- Anisotropic Filtering Algorithm In Java
- Anisotropic Filtering Algorithm Definition
- Anisotropic Filtering Algorithm Examples
- Anisotropic Filtering Nvidia
- Anisotropic Filtering Level
- The option to enable anisotropic filtering is present in almost every PC game on the market today. Usually you will be able to select texture sample rates of 2x, 4x, 8x, or 16x. The texture sample rate is the number of passes the anisotropic filtering algorithm makes on the current textures in the frame.
- Anisotropic filtering algorithm was proposed, which can filter out the background noise while preserve object boundary effectively. The filtering performance was evaluated by comparing that with some other filtering algorithms.
An illustration of texture filtering methods showing a trilinear mipmapped texture on the left and the same texture enhanced with anisotropic texture filtering on the right.
In 3D computer graphics, anisotropic filtering (abbreviated AF) is a method of enhancing the image quality of textures on surfaces of computer graphics that are at oblique viewing angles with respect to the camera where the projection of the texture (not the polygon or other primitive on which it is rendered) appears to be non-orthogonal (thus the origin of the word: 'an' for not, 'iso' for same, and 'tropic' from tropism, relating to direction; anisotropic filtering does not filter the same in every direction).
Anisotropic Filtering of Non-Linear Surface Features Klaus Hildebrandt† Konrad Polthier† Zuse Institute Berlin, Germany‡ Abstract A new method for noise removal of arbitrary surfaces meshes is presented which focuses on the preservation and sharpening of non-linear geometric features such as curved surface regions and feature lines. Anisotropic spatial point patterns and performs equally well in cases that do not explicitly benefit from an anisotropic perspective. ADCN has the same time complexity and similar run time as DBSCAN and OPTICS. Our algorithm is particularly suited for linear features such as typically encountered in urban structures.
Like bilinear and trilinear filtering, anisotropic filtering eliminates aliasing effects,[1][2] but improves on these other techniques by reducing blur and preserving detail at extreme viewing angles.
Anisotropic filtering is relatively intensive (primarily memory bandwidth and to some degree computationally, though the standard space–time tradeoff rules apply) and only became a standard feature of consumer-level graphics cards in the late 1990s.[3] Anisotropic filtering is now common in modern graphics hardware (and video driver software) and is enabled either by users through driver settings or by graphics applications and video games through programming interfaces.
An improvement on isotropic MIP mapping[edit]
An example of anisotropic mipmap image storage: the principal image on the top left is accompanied by filtered, linearly transformed copies of reduced size. (click to compare to previous, isotropic mipmaps of the same image)
From this point forth, it is assumed the reader is familiar with MIP mapping.
If we were to explore a more approximate anisotropic algorithm, RIP mapping, as an extension from MIP mapping, we can understand how anisotropic filtering gains so much texture mapping quality.[4] If we need to texture a horizontal plane which is at an oblique angle to the camera, traditional MIP map minification would give us insufficient horizontal resolution due to the reduction of image frequency in the vertical axis. This is because in MIP mapping each MIP level is isotropic, so a 256 × 256 texture is downsized to a 128 × 128 image, then a 64 × 64 image and so on, so resolution halves on each axis simultaneously, so a MIP map texture probe to an image will always sample an image that is of equal frequency in each axis. Thus, when sampling to avoid aliasing on a high-frequency axis, the other texture axes will be similarly downsampled and therefore potentially blurred.
With MIP map anisotropic filtering, in addition to downsampling to 128 × 128, images are also sampled to 256 × 128 and 32 × 128 etc. These anisotropically downsampled images can be probed when the texture-mapped image frequency is different for each texture axis. Therefore, one axis need not blur due to the screen frequency of another axis, and aliasing is still avoided. Unlike more general anisotropic filtering, the MIP mapping described for illustration is limited by only supporting anisotropic probes that are axis-aligned in texture space, so diagonal anisotropy still presents a problem, even though real-use cases of anisotropic texture commonly have such screenspace mappings.
Although implementations are free to vary their methods, MIP mapping and the associated axis aligned constraints mean it is suboptimal for true anisotropic filtering and is used here for illustrative purposes only. Fully anisotropic implementation is described below.
In layman's terms, anisotropic filtering retains the 'sharpness' of a texture normally lost by MIP map texture's attempts to avoid aliasing. Anisotropic filtering can therefore be said to maintain crisp texture detail at all viewing orientations while providing fast anti-aliased texture filtering.
Degree of anisotropy supported[edit]
Different degrees or ratios of anisotropic filtering can be applied during rendering and current hardware rendering implementations set an upper bound on this ratio.[5] This degree refers to the maximum ratio of anisotropy supported by the filtering process. Bitdefender cracked download. For example, 4:1 (pronounced “4-to-1”) anisotropic filtering will continue to sharpen more oblique textures beyond the range sharpened by 2:1.[6]
In practice what this means is that in highly oblique texturing situations a 4:1 filter will be twice as sharp as a 2:1 filter (it will display frequencies double that of the 2:1 filter). However, most of the scene will not require the 4:1 filter; only the more oblique and usually more distant pixels will require the sharper filtering. This means that as the degree of anisotropic filtering continues to double there are diminishing returns in terms of visible quality with fewer and fewer rendered pixels affected, and the results become less obvious to the viewer.
When one compares the rendered results of an 8:1 anisotropically filtered scene to a 16:1 filtered scene, only a relatively few highly oblique pixels, mostly on more distant geometry, will display visibly sharper textures in the scene with the higher degree of anisotropic filtering, and the frequency information on these few 16:1 filtered pixels will only be double that of the 8:1 filter. The performance penalty also diminishes because fewer pixels require the data fetches of greater anisotropy.
In the end it is the additional hardware complexity vs. these diminishing returns, which causes an upper bound to be set on the anisotropic quality in a hardware design. Applications and users are then free to adjust this trade-off through driver and software settings up to this threshold.
Implementation[edit]
True anisotropic filtering probes the texture anisotropically on the fly on a per-pixel basis for any orientation of anisotropy.
In graphics hardware, typically when the texture is sampled anisotropically, several probes (texel samples) of the texture around the center point are taken, but on a sample pattern mapped according to the projected shape of the texture at that pixel,[7] although earlier software methods have used summed area tables.[8]
Each anisotropic filtering probe is often in itself a filtered MIP map sample, which adds more sampling to the process. Sixteen trilinear anisotropic samples might require 128 samples from the stored texture, as trilinear MIP map filtering needs to take four samples times two MIP levels and then anisotropic sampling (at 16-tap) needs to take sixteen of these trilinear filtered probes.
However, this level of filtering complexity is not required all the time. There are commonly available methods to reduce the amount of work the video rendering hardware must do.
The anisotropic filtering method most commonly implemented on graphics hardware is the composition of the filtered pixel values from only one line of MIP map samples. In general the method of building a texture filter result from multiple probes filling a projected pixel sampling into texture space is referred to as 'footprint assembly', even where implementation details vary.[9][10][11]
Anisotropic Filtering Algorithm In Java
Performance and optimization[edit]
The sample count required can make anisotropic filtering extremely bandwidth-intensive. Multiple textures are common; each texture sample could be four bytes or more, so each anisotropic pixel could require 512 bytes from texture memory, although texture compression is commonly used to reduce this.
A video display device can easily contain over two million pixels, and desired application framerates are often upwards of 60 frames per second. As a result, the required texture memory bandwidth may grow to large values. Ranges of hundreds of gigabytes per second of pipeline bandwidth for texture rendering operations is not unusual where anisotropic filtering operations are involved.[12]
Fortunately, several factors mitigate in favor of better performance:
Anisotropic Filtering Algorithm Definition
- The probes themselves share cached texture samples, both inter-pixel and intra-pixel.[13]
- Even with 16-tap anisotropic filtering, not all 16 taps are always needed because only distant highly oblique pixel fills tend to be highly anisotropic.[6]
- Highly Anisotropic pixel fill tends to cover small regions of the screen (i.e. generally under 10%)[6]
- Texture magnification filters (as a general rule) require no anisotropic filtering.
See also[edit]
References[edit]
- ^Blinn, James F.; Newell, Martin E. (October 1976). 'Graphics and Image Processing: Texture and Reflection in Computer Generated Images'(PDF). Communications of the ACM. 19 (10): 542–547. doi:10.1145/360349.360353. Retrieved 2017-10-20.
- ^Heckbert, Paul S. (November 1986). 'Survey Of Texture Mapping'(PDF). IEEE Computer Graphics and Applications: 56–67. Retrieved 2017-10-20.
- ^'Radeon Whitepaper'(PDF). ATI Technologies Inc. 2000. p. 23. Retrieved 2017-10-20.
- ^'Chapter 5: Texturing'(PDF). CS559, Fall 2003. University of Wisconsin–Madison. 2003. Retrieved 2017-10-20.
- ^'Anisotropic Filtering'. Nvidia Corporation. Retrieved 2017-10-20.
- ^ abc'Texture antialiasing'. ATI's Radeon 9700 Pro graphics card. The Tech Report. Retrieved 2017-10-20.
- ^Olano, Marc; Mukherjee, Shrijeet; Dorbie, Angus (2001). Vertex-based anisotropic texturing(PDF). Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Workshop on Graphics Hardware. pp. 95–98. CiteSeerX10.1.1.1.6886. doi:10.1145/383507.383532. ISBN978-1581134070. Archived from the original(PDF) on 2017-02-14. Retrieved 2017-10-20.
- ^Crow, Franklin C. (July 1984). 'Summed-Area Tables for Texture Mapping'(PDF). SIGGRAPH'84: Computer Graphics. 18 (3). Retrieved 2017-10-20.
- ^Schilling, A.; Knittel, G.; Strasser, W. (May 1996). 'Texram: a smart memory for texturing'. IEEE Computer Graphics and Applications. 16 (3): 32–41. doi:10.1109/38.491183.
- ^Chen, Baoquan; Dachille, Frank; Kaufman, Arie (March 2004). 'Footprint Area Sampled Texturing'(PDF). IEEE Transactions on Visualization and Computer Graphics. 10 (2): 230–240. doi:10.1109/TVCG.2004.1260775. Retrieved 2017-10-20.
- ^Lensch, Hendrik (2007). 'Computer Graphics: Texture Filtering & Sampling Theory'(PDF). Max Planck Institute for Informatics. Retrieved 2017-10-20.
- ^Mei, Xinxin; Chu, Xiaowen (2015-09-08). 'Dissecting GPU Memory Hierarchy through Microbenchmarking'. arXiv:1509.02308 [cs.AR].Accessed 2017-10-20.
- ^Igehy, Homan; Eldridge, Matthew; Proudfoot, Kekoa (1998). 'Prefetching in a Texture Cache Architecture'. Eurographics/SIGGRAPH Workshop on Graphics Hardware. Stanford University. Retrieved 2017-10-20.
External links[edit]
- The Naked Truth About Anisotropic Filtering (2002-09-26)
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In computer graphics, texture filtering or texture smoothing is the method used to determine the texture color for a texture mappedpixel, using the colors of nearby texels (pixels of the texture). There are two main categories of texture filtering, magnification filtering and minification filtering.[1] Depending on the situation texture filtering is either a type of reconstruction filter where sparse data is interpolated to fill gaps (magnification), or a type of anti-aliasing (AA), where texture samples exist at a higher frequency than required for the sample frequency needed for texture fill (minification). Put simply, filtering describes how a texture is applied at many different shapes, size, angles and scales. Depending on the chosen filter algorithm the result will show varying degrees of blurriness, detail, spatial aliasing, temporal aliasing and blocking. Depending on the circumstances filtering can be performed in software (such as a software rendering package) or in hardware for real time or GPU accelerated rendering or in a mixture of both. For most common interactive graphical applications modern texture filtering is performed by dedicated hardware which optimizes memory access through memory cacheing and pre-fetch and implements a selection of algorithms available to the user and developer.
There are many methods of texture filtering, which make different trade-offs between computational complexity, memory bandwidth and image quality.
- 3Filtering methods
The need for filtering[edit]
During the texture mapping process for any arbitrary 3D surface, a texture lookup takes place to find out where on the texture each pixel center falls. For texture-mapped polygonal surfaces composed of triangles typical of most surfaces in 3D games and movies, every pixel (or subordinate pixel sample) of that surface will be associated with some triangle(s) and a set of barycentric coordinates, which are used to provide a position within a texture. Such a position may not lie perfectly on the 'pixel grid,' necessitating some function to account for these cases. In other words, since the textured surface may be at an arbitrary distance and orientation relative to the viewer, one pixel does not usually correspond directly to one texel. Some form of filtering has to be applied to determine the best color for the pixel. Insufficient or incorrect filtering will show up in the image as artifacts (errors in the image), such as 'blockiness', jaggies, or shimmering.
There can be different types of correspondence between a pixel and the texel/texels it represents on the screen. These depend on the position of the textured surface relative to the viewer, and different forms of filtering are needed in each case. Given a square texture mapped on to a square surface in the world, at some viewing distance the size of one screen pixel is exactly the same as one texel. Closer than that, the texels are larger than screen pixels, and need to be scaled up appropriately - a process known as texture magnification. Farther away, each texel is smaller than a pixel, and so one pixel covers multiple texels. In this case an appropriate color has to be picked based on the covered texels, via texture minification. Graphics APIs such as OpenGL allow the programmer to set different choices for minification and magnification filters.[1]
Note that even in the case where the pixels and texels are exactly the same size, one pixel will not necessarily match up exactly to one texel. It may be misaligned or rotated, and cover parts of up to four neighboring texels. Hence some form of filtering is still required.
Mipmapping[edit]
Mipmapping is a standard technique used to save some of the filtering work needed during texture minification.[2] It is also highly beneficial for cache coherency - without it the memory access pattern during sampling from distant textures will exhibit extremely poor locality, adversely affecting performance even if no filtering is performed.
During texture magnification, the number of texels that need to be looked up for any pixel is always four or fewer; during minification, however, as the textured polygon moves farther away potentially the entire texture might fall into a single pixel. This would necessitate reading all of its texels and combining their values to correctly determine the pixel color, a prohibitively expensive operation. Mipmapping avoids this by prefiltering the texture and storing it in smaller sizes down to a single pixel. As the textured surface moves farther away, the texture being applied switches to the prefiltered smaller size. Different sizes of the mipmap are referred to as 'levels', with Level 0 being the largest size (used closest to the viewer), and increasing levels used at increasing distances.
Filtering methods[edit]
This section lists the most common texture filtering methods, in increasing order of computational cost and image quality.
Nearest-neighbor interpolation[edit]
Nearest-neighbor interpolation is the simplest and crudest filtering method — it simply uses the color of the texel closest to the pixel center for the pixel color. While simple, this results in a large number of artifacts - texture 'blockiness' during magnification,[3] and aliasing and shimmering during minification.[4] This method is fast during magnification but during minification the stride through memory becomes arbitrarily large and it can often be less efficient than MIP-mapping due to the lack of spatially coherent texture access and cache-line reuse.[5]
Nearest-neighbor with mipmapping[edit]
This method still uses nearest neighbor interpolation, but adds mipmapping — first the nearest mipmap level is chosen according to distance, then the nearest texel center is sampled to get the pixel color. This reduces the aliasing and shimmering significantly during minification but does not eliminate it entirely. In doing so it improves texture memory access and cache-line reuse through avoiding arbitrarily large access strides through texture memory during rasterization. This does not help with blockiness during magnification as each magnified texel will still appear as a large rectangle.
Linear mipmap filtering[edit]
Less commonly used, OpenGL and other APIs support nearest-neighbor sampling from individual mipmaps whilst linearly interpolating the two nearest mipmaps relevant to the sample.
Bilinear filtering[edit]
Bilinear filtering is the next step up. In this method the four nearest texels to the pixel center are sampled (at the closest mipmap level), and their colors are combined by weighted average according to distance.[6] This removes the 'blockiness' seen during magnification, as there is now a smooth gradient of color change from one texel to the next, instead of an abrupt jump as the pixel center crosses the texel boundary.[7] Bilinear filtering for magnification filtering is common. When used for minification it is often used with mipmapping; though it can be used without, it would suffer the same aliasing and shimmering problems as nearest-neighbor filtering when minified too much. For modest minification ratios, however, it can be used as an inexpensive hardware accelerated weighted texture supersample.
Anisotropic Filtering Algorithm Examples
Trilinear filtering[edit]
Anisotropic Filtering Nvidia
Trilinear filtering is a remedy to a common artifact seen in mipmapped bilinearly filtered images: an abrupt and very noticeable change in quality at boundaries where the renderer switches from one mipmap level to the next. Trilinear filtering solves this by doing a texture lookup and bilinear filtering on the two closest mipmap levels (one higher and one lower quality), and then linearly interpolating the results.[8] This results in a smooth degradation of texture quality as distance from the viewer increases, rather than a series of sudden drops. Of course, closer than Level 0 there is only one mipmap level available, and the algorithm reverts to bilinear filtering.
Anisotropic Filtering Level
Anisotropic filtering[edit]
Anisotropic filtering is the highest quality filtering available in current consumer 3D graphics cards. Simpler, 'isotropic' techniques use only square mipmaps which are then interpolated using bi– or trilinear filtering. (Isotropic means same in all directions, and hence is used to describe a system in which all the maps are squares rather than rectangles or other quadrilaterals.)
When a surface is at a high angle relative to the camera, the fill area for a texture will not be approximately square. Consider the common case of a floor in a game: the fill area is far wider than it is tall. In this case, none of the square maps are a good fit. The result is blurriness and/or shimmering, depending on how the fit is chosen. Anisotropic filtering corrects this by sampling the texture as a non-square shape. The goal is to sample a texture to match the pixel footprint as projected into texture space, and such a footprint is not always axis aligned to the texture. Further, when dealing with sample theory a pixel is not a little square[9] therefore its footprint would not be a projected square. Footprint assembly in texture space samples some approximation of the computed function of a projected pixel in texture space but the details are often approximate,[10] highly proprietary and steeped in opinions about sample theory. Conceptually though the goal is to sample a more correct anisotropic sample of appropriate orientation to avoid the conflict between aliasing on one axis vs. blurring on the other when projected size differs.
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In anisotropic implementations, the filtering may incorporate the same filtering algorithms used to filter the square maps of traditional mipmapping during the construction of the intermediate or final result.
Percentage Closer filtering[edit]
Depth based Shadow mapping can use an interesting Percentage Closer Filter (PCF) with depth mapped textures that broadens one's perception of the kinds of texture filters that might be applied. In PCF a depth map of the scene is rendered from the light source. During the subsequent rendering of the scene this depth map is then projected back into the scene from the position of the light and a comparison is performed between the projective depth coordinate and the fetched texture sample depth. The projective coordinate will be the scene pixels depth from the light but the fetched depth from the depth map will represent the depth of the scene along that projected direction. In this way a determination of visibility to the light and therefore illumination by the light can be made for the rendered pixel. So this texturing operation is a boolean test of whether the pixel is lit, however multiple samples can be tested for a given pixel and the boolean results summed and averaged. In this way in combination with varying parameters like sampled texel location and even jittered depth map projection location a post-depth-comparison average or percentage of samples closer and therefore illuminated can be computed for a pixel. Critically, the summation of boolean results and generation of a percentage value must be performed after the depth comparison of projective depth and sample fetch, so this depth comparison becomes an integral part of the texture filter. This percentage can then be used to weight an illumination calculation and provide not just a boolean illumination or shadow value but a soft shadow penumbra result.[11][12] A version of this is supported in modern hardware where a comparison is performed and a post boolean comparison bilinear filter by distance is applied[13]
See also[edit]
References[edit]
- ^ ab'Chapter 9 - OpenGL Programming Guide'. Glprogramming.com. 2009-02-13. Filtering. Retrieved 2018-01-14.
- ^Williams, Lance (1983). 'Pyramidal parametrics'(PDF). ACM SIGGRAPH Computer Graphics. 17 (3): 1–11. doi:10.1145/964967.801126. ISSN0097-8930.
- ^'Game Engine Design: Texture Mapping'(PDF). uncc.edu. Texture Magnification.
- ^'Game Engine Design: Texture Mapping'(PDF). uncc.edu. Texture Minification.
- ^Hendrik Lensch (2007-11-29). 'Computer Graphics: Texture Filtering & Sampling Theory'(PDF). Max Planck Society. MipMaps. Retrieved 2018-01-14.
- ^Markus Hadwiger (2015-03-09). 'GPU and GPGPU Programming Lecture 12: GPU Texturing 2'(PDF). KAUST. Texture Reconstruction: Magnification.
- ^Markus Hadwiger (2015-03-09). 'GPU and GPGPU Programming Lecture 12: GPU Texturing 2'(PDF). KAUST. Texture Anti-Aliasing: MIP Mapping.
- ^Hendrik Lensch (2007-11-29). 'Computer Graphics: Texture Filtering & Sampling Theory'(PDF). Max Planck Society. MipMapping II. Retrieved 2018-01-14.
- ^Alvy Ray Smith (1995-07-17). 'A Pixel Is Not A Little Square! (And a Voxel is Not a Little Cube) - Technical Memo 6'(PDF). cs.princeton.edu. Retrieved 2018-01-14.
- ^Hendrik Lensch (2007-11-29). 'Computer Graphics: Texture Filtering & Sampling Theory'(PDF). Max Planck Society. Anisotropic Filtering. Retrieved 2018-01-14.
- ^Reeves, William T.; Salesin, David H.; Cook, Robert L. (1987-08-01). 'Rendering antialiased shadows with depth maps'(PDF). ACM SIGGRAPH Computer Graphics. Association for Computing Machinery (ACM). 21 (4): 283–291. doi:10.1145/37402.37435. ISSN0097-8930.
- ^Randima Fernando (2008-07-02). 'Percentage-Closer Soft Shadows'(PDF). NVIDIA Corporation. Retrieved 2018-01-14.
- ^'WebGL WEBGL_depth_texture Khronos Ratified Extension Specification'. Khronos.org. 2014-07-15. Retrieved 2018-01-14.
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