Abstract: According to some embodiments, a technique provides for the execution of an instruction that includes receiving residual data of a first image and decoded pixels of a second image, zero-extending a plurality of unsigned data operands of the decoded pixels producing a plurality of unpacked data operands, adding a plurality of signed data operands of the residual data to the plurality of unpacked data operands producing a plurality of signed results; and saturating the plurality of signed results producing a plurality of unsigned results.

Abstract: According to some embodiments, a device is configured to perform a dual multiply-accumulate operation. In one embodiment, the device includes a functional unit configured to calculate, in parallel, a first multiplication product of a first coefficient and a first sample; and a second multiplication product of the first coefficient and a second sample. The first sample is an (n)th sample and the second sample is an (n+2)th sample in a plurality of sequential samples. The functional unit outputs and stores the first multiplication product and the second multiplication product in different storage locations in at least one storage device.

Abstract: According to some embodiments, a technique provides for the execution of an instruction that includes receiving residual data of a first image and decoded pixels of a second image, zero-extending a plurality of unsigned data operands of the decoded pixels producing a plurality of unpacked data operands, adding a plurality of signed data operands of the residual data to the plurality of unpacked data operands producing a plurality of signed results; and saturating the plurality of signed results producing a plurality of unsigned results.

Abstract: A method, apparatus, and system to scale a color image, the method including determining a color format of image data representative of the color image, the image data being in a pre-processed format and an unprocessed format; and performing a two-dimensional (2-D) image scaling operation on the image data, wherein a plurality of separable one-dimensional filters are applied to the image data to provide a scaled image of the color image and the image scaling operation is the same for the pre-processed formatted image data and the unprocessed formatted image data.

Abstract: A system, apparatus, method and article to encode image signals are described. The apparatus may include a noise determination that determines one or more noise characteristics of an image sensor. In addition, the apparatus may include an encoder module that encodes one or more images received from the image sensor in accordance with one or more encoding settings that are based on the one or more noise characteristics. The noise characteristics may be based on various factors, such as dark pixel value statistics. Other embodiments are described and claimed.

Abstract: A method and apparatus for calculation and storage of Single-Instruction-Multiple-Data (SIMD) saturation history information pursuant to instruction execution. A first coprocessor instruction has a first format identifying a saturating operation, a first source having packed data elements and a second source having packed data elements. The saturating operation is executed on the packed data elements of the first and second sources. Saturation flags are stored in the Wireless Coprocessor Saturation Status Flag (wCSSF) register to indicate if a result of the saturating operation saturated. A second coprocessor instruction has a second format identifying a saturation history processing operation and a saturation data size. An operand for the processing operation is determined based on the saturation data size, and the processing operation is executed on the saturation flags and the operand for the saturation data size.

Abstract: According to some embodiments, motion vector information associated with a set of image blocks is tracked. The tracked information may include motion vector information associated with subsets of the image blocks, and at least some of the subsets may be of different sizes. At least one subset of image blocks may then be adaptively fused into a single image block.

Abstract: Methods and apparatus for calculating Single-Instruction-Multiple-Data (SIMD) complex arithmetic. A coprocessor instruction has a format identifying a multiply and subtract instruction to generate real components for complex multiplication of first operand complex data and corresponding second operand complex data, a cross multiply and add instruction to generate imaginary components for complex multiplication of the first operand complex data and the corresponding second operand complex data, an add-subtract instruction to add real components of the first operand to imaginary components of the second operand and to subtract real components of the second operand from imaginary components of the first operand, and a subtract-add instruction to subtract the real components of the second operand from the imaginary components of the first operand and to add the real components of the first operand to the imaginary components of the second operand.

Abstract: According to some embodiments, a technique provides for the execution of an instruction that includes receiving residual data of a first image and decoded pixels of a second image, zero-extending a plurality of unsigned data operands of the decoded pixels producing a plurality of unpacked data operands, adding a plurality of signed data operands of the residual data to the plurality of unpacked data operands producing a plurality of signed results; and saturating the plurality of signed results producing a plurality of unsigned results.

Abstract: According to some embodiments, a dual multiply-accumulate operation optimized for even and odd multisample calculations is disclosed.

Abstract: Transfer functions are often used for image processing. Look-up tables can be used to implement transfer functions in a processor-efficient manner. In one embodiment, the invention is an apparatus that includes a look-up table (LUT) storing sample outputs from an output range of a transfer function, the sample outputs corresponding to sample inputs from an input range of the transfer function, the sample inputs being distributed so that more sample inputs are associated with a first region of the transfer function than a second region of the transfer function; and an address module to calculate an index into the LUT based on image data. In one embodiment, the apparatus uses the LUT to process the image data.

Abstract: According to some embodiments, a Single-Instruction/Multiple-Data averaging operation is presented. The averaging operation averages multiple sets of data elements, for example, two data elements each from a first source and a second source, producing a set of averages. In at least one embodiment, in a first adder stage, a first plurality of data elements are added to a second plurality of data elements, generating a plurality of intermediate results. In a second adder stage, multiple different combinations of the plurality of intermediate results are added together, generating a plurality of sum results. The two least significant bits of each sum result are discarded.

Abstract: According to some embodiments, a Single-Instruction/Multiple-Data (SIMD) averaging instruction is used to process pixels of image data. The averaging instruction generates a set of four-pixel averages, where each average is generated from two pixels in a first source register and two pixels in a second source register. The first source register contains a plurality of pixels from a first row of pixels and the second source register contains a plurality of pixels from a second row. In one embodiment, the first and second rows are adjacent rows in an image and the averaging instruction is used, for example, to down-scale an image, perform color conversion, and the like. In another embodiment, the first and second rows are from different images and the averaging instruction is used, for example, in motion estimation for video encoding, in motion compensation for video decoding, and the like.

Abstract: Images are obtained for image compression. The images are compared using sum of absolute difference devices, which have arithmetic parts, and accumulators. The sign bits of the accumulators are determined at a time of minimum distortion between two images. These sign bits are associated with sets of probabilistically-similar parts. When other sets from that set are obtained later, an early exit is established.