Encoder and method for encoding of pixel values of a digital image comprising multiple lines of pixels to accomplish lossless compression of the digital image. For each of said multiple lines the encoder obtains unencoded pixels values of the line. Further, for each of said multiple lines, the encoder determines, for each of one or more pixels of the line, which encoding to be used for encoding of the unencoded pixel value of the pixel (x) in said lossless compression of the digital image. The determination being based on how said unencoded pixel value relates to unencoded pixel values of other, closest neighboring pixels (N1, N2) of said line.

There is provided a graphics processing system that allows decompression of a compressed texture with high efficiency. The graphics processing system includes: a main memory; and a graphics processing unit, in which the graphics processing unit includes a run length decoding section adapted to run-length-decode a compressed texture, and a reciprocal spatial frequency conversion section adapted to restore the texture by performing reciprocal spatial frequency conversion on the run-length-decoded texture, and the main memory includes a texture pool adapted to partially cache the restored texture.

There is provided a graphics processing system that allows decompression of a compressed texture with high efficiency. The graphics processing system includes: a main memory; and a graphics processing unit, in which the graphics processing unit includes a run length decoding section adapted to run-length-decode a compressed texture, and a reciprocal spatial frequency conversion section adapted to restore the texture by performing reciprocal spatial frequency conversion on the run-length-decoded texture, and the main memory includes a texture pool adapted to partially cache the restored texture.

An example embodiment may involve obtaining an a×b pixel macro-cell from an input image. Pixels in the a×b pixel macro-cell may have respective pixel values and may be associated with respective tags. It may be determined whether at least e of the respective tags indicate that their associated pixels represent edges in the input image. Based on this determination, either a first encoding or a second encoding of the a×b pixel macro-cell may be selected. The first encoding may weigh pixels that represent edges in the input image heavier than pixels that do not represent edges in the input image, and the second encoding might not consider whether pixels represent edges. The selected encoding may be performed and written to a computer-readable output medium.

An example embodiment may involve obtaining an a×b pixel macro-cell from an input image. Pixels in the a×b pixel macro-cell may have respective pixel values and may be associated with respective tags. It may be determined whether at least e of the respective tags indicate that their associated pixels represent edges in the input image. Based on this determination, either a first encoding or a second encoding of the a×b pixel macro-cell may be selected. The first encoding may weigh pixels that represent edges in the input image heavier than pixels that do not represent edges in the input image, and the second encoding might not consider whether pixels represent edges. The selected encoding may be performed and written to a computer-readable output medium.

Decoding a bitset, each bit of the bitset corresponding to a respective value in a range of a minimum value to a maximum value, includes decoding, from a compressed bitstream, indexes of bits of the bitset, each bit of the bits having a first value. Decoding the bitset also includes setting all other bits of the bitset not decoded from the compressed bitstream to a second value. Decoding the indexes of bits of the bitset includes decoding a number of the indexes of the bits of the bitset, decoding a first index of the indexes in a first range having a first lower bound and a first upper bound, and decoding a last index of the indexes in a second range having a second lower bound and a second upper bound.

Techniques and tools for performing fading compensation in video processing applications are described. For example, during encoding, a video encoder performs fading compensation using fading parameters comprising a scaling parameter and a shifting parameter on one or more reference images. During decoding, a video decoder performs corresponding fading compensation on the one or more reference images.

Techniques and tools for performing fading compensation in video processing applications are described. For example, during encoding, a video encoder performs fading compensation using fading parameters comprising a scaling parameter and a shifting parameter on one or more reference images. During decoding, a video decoder performs corresponding fading compensation on the one or more reference images.

Encoding an image includes determining respective costs of coding a symbol using available coding types. A first coding type indicates that a value of the symbol is to be decoded using a same number of bits, and a second coding type indicates that the value of the symbol is to be decoded using a range. An optimal coding type of the available coding types is selected, which corresponds to a smallest cost of the respective costs. A first indicator of the optimal coding type and a first symbol value of the symbol using the optimal coding type are encoded in a compressed bitstream. Decoding an image includes decoding, from a header of a compressed bitstream, respective coding types of symbols encoded in the compressed bitstream and decoding, from the compressed bitstream, respective values of the symbols according to the respective coding types decoded from the header.

Disclosed are techniques for coding coefficients of a video block having a non-square shape defined by a width and a height, comprising coding one or more of x- and y-coordinates that indicate a position of a last non-zero coefficient within the block according to an associated scanning order, including coding each coordinate by determining one or more contexts used to code the coordinate based on one of the width and the height that corresponds to the coordinate, and coding the coordinate by performing a context adaptive entropy coding process based on the contexts. Also disclosed are techniques for coding information that identifies positions of non-zero coefficients within the block, including determining one or more contexts used to code the information based on one or more of the width and the height, and coding the information by performing a context adaptive entropy coding process based on the contexts.