Abstract:
One embodiment of the present invention sets forth a technique for improving antialiasing quality, while minimizing performance degradation, by adaptively selecting between multisampling and supersampling on a per pixel basis. The resulting performance may be generally comparable to multisampling. At the same time, however, the resulting quality may be generally comparable to supersampling. The antialiasing technique disclosed herein determines whether to use multisampling or supersampling on a particular pixel being rendered, based on the specific coverage of the associated geometry primitive. Because many pixel centers are covered by a geometry primitive, a statistical performance advantage is gained when pixels in a rendered image can be generating using multisampling rather than supersampling. The cases where pixel centers are not covered tend to be less frequent, but are very significant to image quality. High image quality is maintained by rendering these cases using supersampling.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     Embodiments of the present invention relate generally to computer graphics systems and more specifically to coverage adaptive multisampling. 
     2. Description of the Related Art 
     Computer graphics systems render images on a two-dimensional grid of pixels that is characterized by a discrete horizontal and vertical quantization resolution. The images may be displayed on a display device or stored for later use. The finite resolution of a rendered image often results in visual artifacts, known generally as “aliasing” artifacts, when the ability of a viewer to resolve spatial resolution exceeds the finite spatial resolution of the rendered image. The visual artifacts associated with aliasing typically appear as jagged edges on object silhouettes or along the intersection of two or more objects. Very small or thin objects may tend to flicker. Another type of aliasing artifact results when the coloration (shading) of pixels varies greatly over a pixel region but the pixel&#39;s shading is computed without sufficient sampling over the pixel, typically because the shading is computed at a single location within the pixel. This type of shading aliasing produces noisy or flickering shading results, particularly when animation is involved. 
     Techniques for reducing the artifacts associated with aliasing are referred to as “antialiasing” techniques. Supersampling and multisampling are two well-known antialiasing techniques. Supersampling increases the spatial rendering resolution of an image by using multiple samples that are fully rendered for every pixel within the final image. For example, a supersampling system may generate a pixel by combining four samples, each typically including independently textured and shaded color, depth and coverage information. The four samples are combined using well-known techniques to produce one pixel in the final image, which benefits in general from the increased inherent spatial rendering resolution provided by the additional samples. Supersampling also reduces both edge and shading artifacts due to aliasing because both coverage and shading are performed at more than one sample per pixel. 
     When the supersampling system performs texture mapping, each of the four samples within a pixel is usually texture mapped separately according to a specified texture mapping technique. For example, trilinear texture mapping may be used to independently texture each of the four samples, where the center of each sample is used to select a sample location within the associated texture map. The four color values, each generated from eight texels (thirty-two total texels), are combined to generate the color value for the pixel. While supersampling produces very high-quality results, the associated bandwidth and processing load increases in proportion to the number of samples within a pixel, making this technique prohibitively expensive in many scenarios. 
     Multisampling substantially reduces memory bandwidth and processing load relative to supersampling by eliminating the independent color computation for each sample within a pixel (while preserving the independent computation of depth and coverage for each sample). Instead of texturing and shading each sample color independently, one representative sample point is selected for color shading. The resulting color is applied to all samples within the pixel. The underlying assumption of multisampling is that the color of a given shaded object will not change rapidly within the boundaries of a single pixel and therefore using a single representative color sample for the pixel on the object is adequate. However, since intersecting objects may have very different colors within the area of a single pixel, preserving depth and coverage information is important to accurately represent an intersection of two or more objects within the boundaries of the pixel. 
     When a multisampling system performs texture mapping, a representative sample point is selected for the purpose of texture mapping the pixel and the resulting texture map color is attributed to all of the samples within the pixel. Well-known techniques exist for selecting the representative sample point, however the process is fundamentally an approximation. For example, basic multisampling selects the pixel center as the representative sample point for shading the entire pixel. When the texture mapped object is relatively large and parallel with the current view plane of a rendered image, the resulting image quality is generally acceptable because variations in the position of the representative sample point have little effect on the location of the sample point within the texture map. However, as the angle of incidence from the view plane to the surface of the texture mapped object increases, small variations in the position of the representative sample point result is large excursions through the texture map image. For example, if the pixel center is used to define the sample point, but the geometric primitive does not actually intersect the pixel center, then the pixel may be shaded with erroneous texture data. In certain scenarios, such as when “atlas” textures (unrelated image panels consolidated into one flat texture map image) are used, striking visual errors may result when an extrapolated sample point from one texture mapped object strays off the atlas panel and into a panel that has no relationship to the texture mapped object. 
     One well-known technique used to improve image quality of texture mapping in multisampling systems is called “centroid sampling.” Centroid sampling, which is a well-known multisampling technique, attempts to guarantee that the representative sample point is located on a covered portion of the texture mapped object by placing the representative sample at the centroid of covered samples. While centroid sampling improves overall image quality in certain basic instances, this technique is still an approximation and does not completely eliminate artifacts in all common scenarios. For example, objects that occupy one or a small number of screen space pixels may not be properly shaded. 
     In addition, centroid sampling causes texture map address computation resources to generate non-uniformly spaced texture map addresses, rather than evenly spaced texture map addresses that can also be used to compute the partial derivatives needed in level-of-detail (LOD) computations. As a consequence, additional resources are needed to perform LOD computations in a centroid sampling system to avoid artifacts related to erroneous LOD computation. 
     Another approach to improving the image quality in the presence of multisampling is transparency adaptive multisampling. In essence, this approach resorts to supersampling when semi-transparent (non-fully opaque) objects are rendered. The rationale is that transparent objects are often alpha tested. The alpha color component reflects the degree of opacity. When the opacity is below some threshold, such fragments are discarded. However, if the alpha color component, computed as part of a shading operation, is computed once per pixel and shared with all the samples used for multisampling, then all samples for a given pixel are either discarded or kept as a single group. This leads to jagged edges when semi-transparent objects are rendered. To avoid this problem, transparency adaptive multisampling simply resorts to supersampling instead of multisampling when rendering semi-transparent objects. The overall benefit of transparency adaptive multisampling is therefore limited to improving the rendered quality of transparent objects. However, transparency adaptive multisampling introduces a potential performance inefficiency by unnecessarily supersampling pixels for certain rendered objects that have non-opaque and fully opaque regions, as is often the case for objects like trees and vegetation. Additionally, transparency adaptive multisampling does not improve image quality for non-transparent objects subject to aliasing artifacts due to under-sampled shading. Thus, the applicability of transparency adaptive multisampling is limited because this technique adapts the use of supersampling or multisampling on a coarse basis that is specialized for the specific case of transparent objects. 
     As the foregoing illustrates, what is needed in the art is an antialiasing technique that provides the high performance and low resource utilization similar to multisampling, while also providing the high image quality that is comparable with supersampling. 
     SUMMARY OF THE INVENTION 
     One embodiment of the present invention sets forth a method for rendering an antialiased pixel. The method includes the steps of receiving a pixel fragment that includes coverage information for a pixel, determining whether to shade the pixel using a multisampling technique or a supersampling technique based on the coverage information, and computing the color of the pixel using the multisampling technique or the supersampling technique, as determined, based on shading information included in the pixel fragment. 
     One advantage of the disclosed method is that by adaptively selecting between multisampling and supersampling based on coverage information, on a per-pixel basis, higher performance and higher image quality may be achieved relative to prior art approaches. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       So that the manner in which the above recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments. 
         FIG. 1  is a conceptual diagram of a graphics rendering pipeline, according to one embodiment of the invention; 
         FIG. 2  illustrates geometric primitive coverage of pixel quads, according to one embodiment of the invention; 
         FIGS. 3A-3F  illustrate various exemplary coverage scenarios where coverage adaptive multisampling can be used to compute the colors of the different pixels in a pixel quad; 
         FIG. 4  is a flow diagram of method steps for adaptively determining the antialiasing mode of a pixel, according to one embodiment of the invention; and 
         FIG. 5  is a conceptual diagram of a computing device configured to implement one or more aspects of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     The present invention improves the quality of antialiasing in a graphics rendering engine by adaptively selecting between multisampling and supersampling on a per pixel basis. The resulting performance is very good and is generally comparable to multisampling. At the same time, the resulting quality is very good and is generally comparable to supersampling. 
       FIG. 1  is a conceptual diagram of a graphics rendering pipeline  100 , according to one embodiment of the invention. The graphics rendering pipeline  100  includes, without limitation, a geometric processing unit  110 , a rasterization unit  112 , a shader unit  114 , a raster operations unit  116 , and a frame buffer  118 . 
     The geometry processing unit  110  receives geometry objects, typically three-dimensional triangles, from a graphics application (not shown) and conducts geometric transforms as specified by the graphics application. The output of the geometry processing unit  110  includes geometric primitives  120 , such as triangles, that are transformed and projected onto a two-dimensional surface, referred to as “screen space.” Screen space may correspond to a region on a viewer&#39;s display screen used to display rendered images. Alternately, a two-dimensional surface in screen space may correspond to a destination rendering surface in applications that do not immediately display rendered frame buffer data to a screen. Such applications may render, for example, to a video clip that is stored before being viewed. 
     The geometric primitives  120  are distributed to one or more rasterization units  112 . The rasterization unit  112  converts the geometric primitives  120  into fragments  122 , corresponding to screen space pixels that are least partially covered by the geometric primitives. In decomposing geometric primitives  120  into fragments  122 , the rasterization unit  112  determines the screen space pixel coverage of each geometric primitive along with the sample coverage of each fragment. Additionally, the rasterization unit  112  determines the screen space coverage and alignment of each geometric primitive  120 . The rasterization unit  112  generates output data that includes, without limitation, fragments  122  that include geometric coverage and depth information. 
     The shader unit  114  receives fragments from the rasterization unit  112  and processes the fragments into shaded pixels  124 , according to shading instructions specified by the graphics application. The shaded pixels  124  are transmitted to the raster operations unit  116  for further processing. The raster operations unit  116  performs any needed blending on the shaded pixels or samples, as specified by the graphics application, and generates pixel data  126  that is transmitted to the frame buffer  118  for storage and display. 
     The frame buffer  118  includes, without limitation, buffers for depth information and buffers for color information. The frame buffer  118  is typically structured as a two-dimensional surface mapped into linear memory space. 
     Persons skilled in the art will recognize that the present invention is not limited in any way by the architecture of  FIG. 1 . In particular, the teachings of the present invention are equally applicable in graphics rendering pipelines having one or more geometry processing units, one or more rasterization units, one or more shaders, one or more raster operations units and one or more frame buffers. For this reason, the remainder of the description may include references to particular elements of the graphics rendering pipeline in either singular or plural form without any intention to limit the scope of the present invention. 
       FIG. 2  illustrates geometric primitive coverage of pixel quads, according to one embodiment of the invention. A geometric primitive  210 , in this case a triangle, is projected onto a two-dimensional grid of pixels  200 . A given pixel may be fully covered, partially covered, or not covered at all by the geometric primitive  210 . Pixels that are not covered at all typically do not require further processing. Pixels that are fully covered or partially covered are processed further according to certain discard techniques (such as depth sorting and stencil testing) and shading techniques (such as texture mapping). Pixel coverage may be determined according to well-known techniques. One such technique divides the area of a pixel into regions, each with an associated sample point. If the geometric primitive  210  covers a sample point, that region is deemed to be “covered.” For example, the pixel may include five sample points. A first sample point may be situated in the center of the pixel. The remaining four sample points may be distributed about the pixel center in a specific pattern. 
     Certain graphics rendering pipelines increase overall throughput by processing two or more pixels in parallel. For example, the graphics rendering pipeline  100  may process four pixels in parallel, where the four pixels are organized as a two-by-two pixel area called a “pixel quad.” Pixel quads  220 ,  230  and  240  depict three different coverage scenarios, illustrated in greater detail in  FIGS. 3A ,  3 B, and  3 C, respectively. 
       FIG. 3A  illustrates geometric primitive coverage of a pixel quad  220  for the case where the samples of every pixel are fully covered by the geometric primitive  210 . As shown, the four pixels in the pixel quad  220  are considered to be fully covered because all samples  322 ,  324 ,  326  and  328  within the associated pixels are covered by geometric primitive  210 . In this scenario, multisampling may be used to compute the color of each pixel in the pixel quad. That is, the color of each pixel in the pixel quad may be computed using center samples  322 - 0 ,  324 - 0 ,  326 - 0  and  328 - 0 . 
       FIG. 3B  illustrates geometric primitive coverage of a pixel quad  230  for the case where samples  334  and  338  are not fully covered by the geometric primitive  210 , but the center samples  332 - 0 ,  334 - 0 ,  336 - 0  and  338 - 0  of the four different pixels are all covered. In this scenario, multisampling may again be used to compute the color of each pixel in the pixel quad using center samples  332 - 0 ,  334 - 0 ,  336 - 0  and  338 - 0 . 
       FIG. 3C  illustrates geometric primitive coverage of a pixel quad  240  for the case where certain samples are covered by the geometric primitive  210 , but none of the center samples  342 - 0 ,  344 - 0 ,  346 - 0 ,  348 - 0  is covered. As shown, only samples  348 - 2  and  348 - 4  are covered. In this scenario, supersampling with samples  348 - 2  and  248 - 4  may be used to compute the color of the partially covered pixel. The other pixels of the pixel quad  240  do not need further processing since they are not covered by the geometric primitive  210 . 
       FIGS. 3A-3C  illustrate three different scenarios of pixel coverage within a pixel quad, as depicted in  FIG. 2 .  FIGS. 3D-3F  illustrate other exemplary pixel coverage scenarios that may exist within a pixel quad. 
       FIG. 3D  illustrates geometric primitive coverage of a pixel quad  350  for the case where three center samples  352 - 0 ,  354 - 0  and  356 - 0  are covered by a geometric primitive  351 , but none of the samples  358  is covered. In this scenario, multisampling may be used to compute the color of each of the three covered pixels in the pixel quad  350  using center samples  352 - 0 ,  354 - 0  and  356 - 0 . Since none of the samples  358  is covered, the associated pixel requires no further processing. 
       FIG. 3E  illustrates geometric primitive coverage of a pixel quad  360  for the case where three center samples  362 - 0 ,  364 - 0  and  366 - 0  are covered by a geometric primitive  361 , center sample  368 - 0  is not covered, but sample  368 - 1  is covered. In this scenario, a hybrid of multisampling and supersampling may be used to compute the colors of the pixels in the pixel quad  360 . Multisampling may be used to compute the color of each of the three covered pixels in the pixel quad  360  using center samples  362 - 0 ,  364 - 0  and  366 - 0 . Supersampling using sample  368 - 1  may be used to compute the color of the one pixel not having a covered pixel center. 
       FIG. 3F  illustrates geometric primitive coverage of a pixel quad  370  for the case where all pixels are partially covered by a geometric primitive  371 , but no center sample is covered. Since none of the center samples  372 - 0 ,  374 - 0 ,  376 - 0  and  378 - 0  is covered by the geometric primitive  371 , multisampling is not used. Rather, pure supersampling using samples  372 - 4 ,  374 - 4 ,  376 - 1  and  378 - 1  may be used to compute the colors of the respective pixels in the pixel quad  370 . 
       FIGS. 3A-3F  conceptually illustrate how coverage adaptive multisampling can be used to compute the colors of the pixels in a pixel quad. As described below in  FIG. 4 , the decision of whether to use multisampling (based, for example, on one covered center sample) or supersampling (based on a set of covered distributed samples) to compute the color for a particular pixel is based on the coverage of a geometric primitive relative to the individual pixel. 
       FIG. 4  is a flow diagram of method steps for adaptively determining the antialiasing mode of a pixel, according to one embodiment of the invention. Although the method steps are described in conjunction with the systems of  FIGS. 1 and 5 , persons skilled in the art will understand that any system that performs the method steps, in any order, is within the scope of the invention. 
     The method begins in step  410 , where the shader unit  114  receives a pixel fragment for processing a pixel. As is well-known, the pixel fragment includes information such as the coverage information for the pixel as well as shading information. In step  420 , the shader unit  114  examines the center sample of the pixel for coverage. If the center sample is covered, then the method proceeds to step  430 , where the shader unit  114  computes the pixel color using a multisampling technique. The method proceeds to step  450 . In step  450 , the shader unit  114  determines whether the last pixel associated with current primitive has been processed. If all pixels have been processed, then the method terminates in step  490 . If all pixels have not yet been processed, then the method returns to step  410 . 
     Returning now to step  420 , if the shader unit  114  determines that the center sample is not covered, then the method proceeds to step  440 , where the shader unit  114  computes the pixel color using a supersampling technique. The method then proceeds to step  450 , as described above. 
       FIG. 5  is a conceptual diagram of a computing device  500  configured to implement one or more aspects of the present invention. The computing device  500  includes, without limitation, a processor  510 , system memory  520 , a graphics processing unit (GPU)  530  and local memory  540  coupled to the GPU  530 . The GPU  530  includes at least one rendering engine  535  that, in turn, includes at least one graphics rendering pipeline  100  used to process data, as described above. In alternate embodiments, the processor  510 , GPU  530 , local memory  540 , system memory  520 , or any combination thereof, may be integrated into a single processing unit. Furthermore, the functionality of GPU  530  may be included in a chipset or in some other type of special purpose processing unit or co-processor. Persons skilled in the art will recognize that any system having one or more processing units configured to implement the teachings disclosed herein falls within the scope of the present invention. Thus, the architecture of computing device  500  in no way limits the scope of the present invention. 
     In sum, the coverage of a geometric primitive on a pixel being rendered determines which of two antialiasing strategies are used to compute the final color of the pixel. If the pixel center is covered, then the pixel color is computed according to the color of the pixel center. However, if the pixel center is not covered, then supersampling is used to compute the color of the pixel. By adaptively selecting between multisampling and supersampling, on a per-pixel basis, higher performance and higher image quality may be achieved overall. 
     While the determination of whether to use multisampling or supersampling described above is based on whether or not the pixel center is covered, other criteria based on the coverage can be considered as well. For example, the decision could be based on the percentage of samples covered compared to a fixed or programmable threshold. Additionally, the determination could be influenced by other modes within the graphics pipeline, such as whether alpha testing (typically enabled in conjunction with semi-transparent objects) is enabled. The determination may also control the number of samples shaded for the pixel. 
     Embodiments of the present invention may be implemented as a program product for use with a computer system. The program(s) of the program product defines functions of the embodiments (including the methods described herein) and can be contained on a variety of computer-readable storage media. Illustrative computer-readable storage media include, but are not limited to: (i) non-writable storage media (e.g., read-only memory devices within a computer such as CD-ROM disks readable by a CD-ROM drive) on which information is permanently stored; (ii) writable storage media (e.g., floppy disks within a diskette drive or hard-disk drive) on which alterable information is stored. Such computer-readable storage media, when carrying computer-readable instructions that direct the functions of the present invention, are embodiments of the present invention. 
     While the forgoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. For example, much of the above description references “multisampling” and “supersampling” techniques. Persons skilled in the art will understand that the teachings of the present invention extend to any such techniques, including, without limitation, centroid sampling and center sampling. The scope of the present invention is therefore determined by the claims that follow.