A raster unit is configured to generate different sample patterns for adjacent pixels within a given frame. In addition, the raster unit may adjust the sample patterns between frames. The raster unit includes an index unit that selects a sample pattern table for use with a current frame. For a given pixel, the index unit extracts a sample pattern from the selected sample pattern table. The extracted sample pattern is used to generate coverage information for the pixel. The coverage information for all pixels is then used to generate an image. The resultant image may then be filtered to reduce or remove artifacts induced by the changing of sample locations.

One embodiment provides for a data processing system comprising a memory module to store a multisample render target, the multisample render target to store multiple sample locations for each pixel in a set of pixels and a general-purpose graphics processor including a hardware graphics rendering pipeline to generate pixel color data to be output to the multisample render target, a multisample antialiasing compressor to request allocation of one or more planes to store color data for a set of sample locations of a pixel in the set of pixels, and a memory allocator to allocate memory to store color data associated with the multisample render target. The memory allocator can merge a memory allocation for multiple pixels having a sample associated with a same color value.

An embodiment of a parallel processor apparatus may include a sample pattern selector to select a sample pattern for a pixel, and a sample pattern subset selector communicatively coupled to the sample pattern selector to select a first subset of the sample pattern for the pixel corresponding to a left eye display frame and to select a second subset of the sample pattern for the pixel corresponding to a right eye display frame, wherein the second subset is different from the first subset. Other embodiments are disclosed and claimed.

A digital camera comprising a digital image sensor and at least one corrective lens element configured to reduce a blurring of an image in a horizontal or vertical dimension on the digital image sensor. The digital image sensor may be larger than a 28 millimeter diagonal.

Described herein is a data processing system having a multisample antialiasing compressor coupled to a texture unit and shader execution array. In one embodiment, the data processing system includes a memory device to store a multisample render target, the multisample render target to store color data for a set of sample locations of each pixel in a set of pixels; and general-purpose graphics processor comprising a multisample antialiasing compressor to apply multisample antialiasing compression to color data generated for the set of sample locations of a first pixel in the set of pixels and a multisample render cache to store color data generated for the set of sample locations of the first pixel in the set of pixels, wherein color data evicted from the multisample render cache is to be stored to the multisample render target.

Systems, apparatuses and methods may provide for technology that identifies, at an image post-processor, unresolved surface data and identifies, at the image post-processor, control data associated with the unresolved surface data. Additionally, the technology may resolve, at the image post-processor, the unresolved surface data and the control data into a final image.

An apparatus and method for performing multisampling anti-aliasing. For example, one embodiment of an apparatus samples multiple locations within each pixel of an image frame to generate a plurality of image slices. Each image slice comprises a different set of samples for each of the pixels of the image frame. Anti-aliasing is then performed on the image frame using the image slices by first subdividing the plurality of image slices into equal-sized pixel blocks and determining whether each pixel block has one or more different pixel values in different image slices. If so, then edge detection and simple shape detection is performed using pixel data from a pixel block in a single image slice; if not, then edge detection and simple shape detection is performed using the pixel block in multiple image slices.

An image anti-aliasing method comprises following steps: receiving an aliasing image; wherein the aliasing image includes a plurality of source pixels; generating a plurality of hash values corresponding to the plurality of source pixels respectively; and performing a filtering processing or a filter generating procedure on the aliasing image according to the plurality of hash values. Each of the plurality of hash values is generated by the following steps: selecting one source pixel from the aliasing image and selecting a window containing the selected source pixel; determining an aliasing strength according to the grayscale values of all the source pixels of a row and a column at which the selected source pixel is located in the window; and determining a hash value of the selected source pixel according to the aliasing strength.

According to the invention, a method for reducing aliasing artifacts in foveated rendering is disclosed. The method may include accessing a high resolution image and a low resolution image corresponding to the high resolution image, and calculating a difference between a pixel of the high resolution image and a sample associated with the low resolution image. The sample of the low resolution image corresponds to the pixel of the high resolution image. The method may further include modifying the pixel to generate a modified pixel of the high resolution image based on determining that the difference is higher than or equal to a threshold value. The modification may be made such that an updated difference between the modified pixel and the sample is smaller than the original difference.

A graphics processing hardware pipeline is arranged to perform an edge test or a depth calculation. Each hardware arrangement includes a microtile component hardware element, multiple pixel component hardware elements, one or more subsample component hardware elements and a final addition and comparison unit. The microtile component hardware element calculates a first output using a sum-of-products and coordinates of a microtile within a tile in the rendering space. Each pixel component hardware element calculates a different second output using the sum-of-products and coordinates for different pixels defined relative to an origin of the microtile. The subsample component hardware element calculates a third output using the sum-of-products and coordinates for a subsample position defined relative to an origin of a pixel. The adders sum different combinations of the first output, a second output and a third output to generate output results for different subsample positions defined relative to the origin of the tile.