Apple Inc.

Innovation Management Sciences

Other

Maxim Integrated Products, Inc.

Geo Semiconductor Inc.

Simon Wolfenden Butler

Guy Cote

Joseph P Bratt

Chad Edward Fogg

Joseph Anthony Petolino, Jr

Richard W Webb

Diego Garrido

D Amnon Silverstein

Suk Hwan Lim

Sheng Lin

Sorin Constantin Cismas

José Roberto Alvarez

David R Pope

Mark Zimmer

Christopher L Mills

David Hayward

Maxim W Smirnov

Systems and methods for down-scaling are provided. In one example, a method for processing image data includes determining a plurality of output pixel locations using a position value stored by a position register, using the current position value to select a center input pixel from the image data and selecting an index value, selecting a set of input pixels adjacent to the center input pixel, selecting a set of filtering coefficients from a filter coefficient lookup table using the index value, filtering the set of source input pixels to apply a respective one of the set of filtering coefficients to each of the set of source input pixels to determine an output value for the current output pixel at the current position value, and correcting chromatic aberrations in the set of source input pixels.

Raw scaler with chromatic aberration correction

Embodiments of the present disclosure generally relate to image signal processing logic, and in particular, to separating an undecimated image signal data to create two components with lower resolution and full-resolution, generating an interpolation guidance information based on the two components created by separation, forming a difference image data representing the difference between the chroma and luma values of each pixel and its neighboring pixels, and merging the processed image data from the processing pipelines with the unprocessed image data using the interpolation guidance information generated. The generation of the interpolation guidance information is based on determining distances between pixel values from a group comprising pixels from interpolation nodes, pixels diagonally located adjacent to the interpolation nodes, pixels horizontally adjacent to the interpolation nodes, and pixels vertically adjacent to the interpolation nodes.

Separating sub-band image data for processing and merging with unprocessed image data

In some embodiments, a motion estimation search window cache is adaptively re-organized according to frame properties including a frame width and a number of reference frames corresponding to the current frame to be encoded/decoded. The cache reorganization may include an adaptive mapping of reference frame locations to search window cache allocation units (addresses). In some embodiments, a search window is shaped as a quasi-rectangle with truncated upper left and lower right corners, having a full-frame horizontal extent. A search range is defined in a central region of the search window, and is laterally bounded by the truncated corners.

Adaptive motion estimation cache organization

An output rescale module may determine an estimated set of lines to hold in vertical support for use when performing image transformations. For example, an output rescale module may monitor input Y coordinates (in terms of input pixel lines) computed over previous lines and compute a set of lines to hold in a set of line buffers. As each output pixel line is generated, the output rescale module may compute the minimum and maximum values of Y generated by the transform across that line. The minimum and maximum input Y coordinates may then be averaged to determine the center value (the centermost input line) for that output line. The difference (in terms of input pixel lines) between centerlines for two adjacent output lines may be added to the centerline value for the current output line to estimate a center line for the next (not yet generated) output pixel line.

Auto filter extent management

Systems and methods for processing YCC image data provided. In one example, an electronic device includes memory to store image data in RGB or YCC format and a YCC image processing pipeline to process the image data. The YCC image processing pipeline may include receiving logic configured to receive the image data in RGB or YCC format and color space conversion logic configured to, when the image data is received in RGB format, convert the image data into YCC format. The YCC image processing logic may also include luma sharpening and chroma suppression logic; brightness, contrast, and color adjustment logic; gamma logic; chroma decimation logic; scaling logic; and chroma noise reduction logic.

Systems and methods for YCC image processing

Systems and methods for correcting geometric distortion are provided. In one example, an electronic device may include an imaging device, which may obtain image data of a first resolution, and geometric distortion and scaling logic. The imaging device may include a sensor and a lens that causes some geometric distortion in the image data. The geometric distortion correction and scaling logic may scale and correct for geometric distortion in the image data by determining first pixel coordinates in uncorrected or partially corrected image data that, when resampled, would produce corrected output image data at second pixel coordinates. The geometric distortion correction and scaling logic may resample pixels around the image data at the first pixel coordinates to obtain the corrected output image data at the second pixel coordinates. The corrected output image data may be of a second resolution.

Image signal processing involving geometric distortion correction

Systems and methods for processing raw image data are provided. One example of such a system may include memory to store image data in raw format from a digital imaging device and an image signal processor to process the image data. The image signal processor may include data conversion logic and a raw image processing pipeline. The data conversion logic may convert the image data into a signed format to preserve negative noise from the digital imaging device. The raw image processing pipeline may at least partly process the image data in the signed format. The raw image processing pipeline may also include, among other things, black level compensation logic, fixed pattern noise reduction logic, temporal filtering logic, defective pixel correction logic, spatial noise filtering logic, lens shading correction logic, and highlight recovery logic.

Systems and methods for raw image processing

An apparatus includes a first preprocessor circuit and a second preprocessor circuit. The first preprocessor circuit may be configured to generate a first control signal for each of a plurality of macroblocks of an input image based upon a plurality of statistics for each of the plurality of macroblocks. The second preprocessor circuit may be configured to generate a second control signal based upon a combination of the first control signals of a number of macroblocks of the plurality of macroblocks.

Method and apparatus for frame, field and macroblock adaptive progressive/interlace coding selection

An apparatus including a first circuit and a second circuit. The first circuit may be configured to generate a first control signal, a second control signal and a third control signal in response to a first interlaced video signal. The second circuit may be configured to generate a second interlaced video signal in response to the first interlaced video signal, the first control signal, the second control signal and the third control signal. The second circuit may be further configured to vertically scale the first interlaced video signal in an extended vertical domain.

Method and/or architecture for interlaced video resampling and color format conversion using combined vertical-temporal resolution extensions

A method of enhancing picture quality of a video signal is disclosed. The method comprises the steps of generating a interpolated base frame image; receiving a first previously decoded difference picture; receiving a second previously decoded difference picture; generating a combined motion compensated difference surface; and generating a temporally interpolated enhanced picture based upon the interpolated base frame image and the combined motion compensated difference surface. A circuit for enhancing picture quality of a video signal is also disclosed. The circuit comprising a base decoder generating a base image of a standard definition picture; a temporal predictive interpolator coupled to the base decoder and generating an interpolated block; and a summing circuit coupled to the temporal predictive interpolated. The summing circuit preferably adds the interpolated block and a difference block.

Predictive interpolation of a video signal

A method of enhancing picture quality of a video signal is disclosed. The method comprises the steps of receiving base layer images of standard definition pictures from a base layer decoder; defining image areas of the standard definition pictures; classifying image areas into image types by assigning a class number; and generating enhanced pictures based upon the standard definition pictures and the classification of the image areas. A circuit for enhancing picture quality of a video signal is also disclosed. The circuit comprising a base layer decoder; a classifier coupled to the base layer decoder, the classifier generating a class number for image areas of a standard definition picture; a summing circuit coupled to the classifier; an exchange stream decoder coupled to the summing circuit, the exchange stream decoder generating an index; and a codebook table coupled to the summing circuit. The codebook table preferably stores a plurality of codevectors based upon the class number and the index.

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San Rafael, CA, United States of America

Simon Wolfenden Butler