Abstract: Methods and systems for reducing the appearance of block-related artifacts are described. The methods include obtaining image frames in a sequence of image frames and adjusting some or all image frames in the sequence of image frames to generate adjusted image frames. The adjusted image frames may be created by generating image data and adding it to one or more edges of the image frame or by discarding image data from the image frame. The adjusted image frames shift a block origin relative to image data in the image frame. The adjusting is performed so that the shift of the block origin varies during the sequence of image frames. A block-based process is applied to each adjusted image frame to generate processed image frames, wherein blocks of image data are selected and processed in each adjusted frame of image data according to the block origin.

Abstract: The present disclosure relates to a method of contrast-based autofocus for an image capture device, the method comprising: obtaining first sensor data representative of a first contrast characteristic of one or more images captured with a first focus setting, the first sensor data comprising first data values from respective image zones of the one or more images, an image zone being a region of an image; obtaining second sensor data representative of a second contrast characteristic of the one or more images, the second sensor data comprising second data values from respective image zones of the one or more images; processing the first sensor data by performing a first filtering operation on the first sensor data to obtain a first contrast characteristic metric, the first filtering operation being determined by the first contrast characteristic and based on the first sensor data of at least one image zone on a first image of the one or more images and one or more image zones related to the at least one image

Abstract: A method of image processing. The method comprises obtaining a set of image data, the set being associated with one or more parameters representative of one or more image capture characteristics for the set and comprising pixel intensity values representing image pixels having respective pixel locations in an image. The method comprises, for a given pixel intensity value in the set: determining an estimated noise value based on at least: the one or more parameters associated with the set, and a representative intensity value derived from one or more pixel intensity values in the set. The method comprises associating the estimated noise value with the given pixel intensity value.

Abstract: Image data includes a plurality of data values arranged in two or more sequences, each sequence comprising a first number of data positions each having a data value of the plurality, and each data value comprising a second number of bits. Upon receiving each sequence of the two or more sequences, the data values of the sequence are processed to determine, for each given data position of the first number of data positions, a representative value for the given data position based on a relationship between the data value at the given data position and the data value at one or more neighbouring data positions.

Abstract: A method of data processing in a data processing system comprising a computer vision system. The method comprises obtaining image data representative of a plurality of pixels of an image, the image data comprising a plurality of pixel intensity values respectively representing said pixels. The method comprises identifying one or more compromised pixel intensity values in the plurality of pixel intensity values. The method comprises generating sensor defect state data relating to the identified compromised pixel intensity values. The method comprises performing, using the computer vision system, a feature recognition process on the image data. The method comprises performing an action based on the sensor defect state data.

Abstract: A method of processing color filter array, CFA, image data comprising receiving CFA image data comprising a plurality of pixel values in a frame of image data representable as a main two-dimensional row-columnar pattern, each pixel value corresponding to a color filter in a CFA. Different pixel values of the plurality of pixel values are associated with respective different filter colors including first pixel values associated with a first filter color and second pixel values associated with a second filter color. The first pixel values are arranged in at least a two-dimensional checkerboard sub-pattern in the main two-dimensional row-columnar pattern. The method involves performing a diagonally-aligned processing operation on the first pixel values, wherein the processing operation operates on the first pixel values in accordance with a reprojected array, the reprojected array corresponding to a reprojection of the two-dimensional checkerboard sub-pattern into a row-columnar array.

Abstract: The present disclosure relates to a method of processing image data at an apparatus having an image sensor, a first statistics data module and a first processor component, the method comprising: obtaining, at the first statistics data module from the image sensor, first image sensor data; generating, at the first statistics data module, statistics data of a first type derived, at least in part, from the first image sensor data; processing, at the first processor component, the statistics data of the first type to determine whether or not an event is detected in a scene; generating, at the first processor component, an event signal when an event is detected.

Abstract: A method of processing image data, the image data comprising a plurality of data values arranged in two or more sequences, each sequence comprising a first number of data positions each having a data value of the plurality, and each data value comprising a second number of bits, the method comprising: upon receiving each sequence of the two or more sequences, processing the data values of the sequence to determine, for each given data position of the first number of data positions, a representative value for the given data position based on a relationship between the data value at the given data position and the data value at one or more neighbouring data positions.

Abstract: The present disclosure relates to a method of contrast-based autofocus for an image capture device, the method comprising: obtaining first sensor data representative of a first contrast characteristic of one or more images captured with a first focus setting, the first sensor data comprising first data values from respective image zones of the one or more images, an image zone being a region of an image; obtaining second sensor data representative of a second contrast characteristic of the one or more images, the second sensor data comprising second data values from respective image zones of the one or more images; processing the first sensor data by performing a first filtering operation on the first sensor data to obtain a first contrast characteristic metric, the first filtering operation being determined by the first contrast characteristic and based on the first sensor data of at least one image zone on a first image of the one or more images and one or more image zones related to the at least one image

Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, techniques to process pixel values sampled from a multi color channel imaging device. In particular, methods and/or techniques to process pixel samples for interpolating pixel values for one or more color channels.

Abstract: A method and apparatus for processing image data is provided. The method comprises receiving decompressed accumulated image data that has been subjected to a lossy compression algorithm. The accumulated image data includes an accumulated frame of image data and a corresponding plurality of blending coefficients. The blending coefficients are updated by identifying an image feature associated with at least one pixel location of the accumulated frame of image data. The updated blending coefficients and decompressed accumulated frame of image data are sent to a temporal noise reducer, which is configured to use the updated blending coefficients to combine the decompressed accumulated frame of image data with a newly received frame of image data to generate an output image.

Abstract: An image processing method processes color image data. The applies an operator to a representative pixel value to generate a transformed pixel value. A controlled gain is determined so that: if applying a gain based on the transformed pixel value to a maximum color channel value of the pixel will generate a color channel value that is below a threshold value, the controlled gain is determined based on the transformed pixel value and the representative pixel value, and if applying a gain based on the transformed pixel value to the maximum color channel value will generate a color channel value that is above the threshold value, the controlled gain is determined such that the maximum color channel value is mapped to a value representable by a predetermined number of bits. The controlled gain is applied to each of the color channel values.

Abstract: A method for detecting defective pixel values determines an isotropic dispersion difference value by determining a ratio or difference between a pixel error and an isotropic dispersion, where the isotropic dispersion is a measure of how much pixel values in a set of neighbouring pixel values uniformly distributed around the pixel under consideration vary. The method compares the isotropic dispersion difference value to an isotropic threshold. A directional dispersion difference value is found by determining a ratio or difference between a pixel error and a directional dispersion, wherein the directional dispersion is a weighted measure of how much pixel values in a set of neighbouring pixel values around the pixel under consideration in a given direction vary. The directional dispersion difference value is compared to a directional threshold and it is determined that the pixel under consideration is defective based on at least one of the comparison results.

Abstract: A method for compressing data representative of a mapping for use in image processing. The method comprises determining, based on a plurality of mappings representing a look-up table, parameters of a function for transforming a given set of input pixel attribute values into a set of estimated output pixel attribute values. The method comprises, for a plurality of the sets of input pixel attribute values, determining, based on the function and the set of input pixel attribute values, a set of approximate values of the associated set of output pixel attribute values, and determining, based on the associated set of output pixel attribute values and the set of approximate values, a set of residual output pixel attribute values. The method comprises storing data representative of the parameters of the function and data representative of the sets of residual output pixel attribute values.

Abstract: A method for processing an image comprising image data. The image data comprises pixel intensity values, said pixel intensity values being associated with respective pixel locations. For a plurality of zones of the image, based on a plurality of pixel intensity values in the respective zone of the image, a value of a characteristic pertaining to the plurality of pixel intensity values, is determined. At least a spatial filtering process is performed on data representative of the values of the characteristic for the plurality of zones, to obtain filtered values of an image characteristic at respective locations. The filtered values are interpolated from to determine a local value of the image characteristic at a said pixel location. The determining and/or the interpolating is performed using fixed function circuitry. The spatial filtering process is performed using a programmable processor.

Abstract: Methods and systems for reducing the appearance of block-related artifacts are described. The methods include obtaining image frames in a sequence of image frames and adjusting some or all image frames in the sequence of image frames to generate adjusted image frames. The adjusted image frames may be created by generating image data and adding it to one or more edges of the image frame or by discarding image data from the image frame. The adjusted image frames shift a block origin relative to image data in the image frame. The adjusting is performed so that the shift of the block origin varies during the sequence of image frames. A block-based process is applied to each adjusted image frame to generate processed image frames, wherein blocks of image data are selected and processed in each adjusted frame of image data according to the block origin.

Abstract: A method of image processing. The method comprises obtaining a set of image data, the set being associated with one or more parameters representative of one or more image capture characteristics for the set and comprising pixel intensity values representing image pixels having respective pixel locations in an image. The method comprises, for a given pixel intensity value in the set: determining an estimated noise value based on at least: the one or more parameters associated with the set, and a representative intensity value derived from one or more pixel intensity values in the set. The method comprises associating the estimated noise value with the given pixel intensity value.

Abstract: A method of data processing in a data processing system comprising a computer vision system. The method comprises obtaining image data representative of a plurality of pixels of an image, the image data comprising a plurality of pixel intensity values respectively representing said pixels. The method comprises identifying one or more compromised pixel intensity values in the plurality of pixel intensity values. The method comprises generating sensor defect state data relating to the identified compromised pixel intensity values. The method comprises performing, using the computer vision system, a feature recognition process on the image data. The method comprises performing an action based on the sensor defect state data.

Abstract: A first neural network generates a first output tensor based on an input tensor, the first output tensor comprising values to impart an effect to one or more features in the input tensor. A second neural network generates a second output tensor based on the input tensor, and the effect to be imparted to the one or more features is modulated, based at least in part, on the second output tensor.

Abstract: An image processing method including obtaining image data. The image data includes a plurality of image data values. The image processing method also includes processing the image data, thereby generating output data. Processing the image data includes applying a convolution operation to the plurality of image data values using a kernel including a plurality of coefficients. Applying the convolution operation includes obtaining a sum of image data values of the plurality of image data values that correspond respectively to coefficients of the plurality of coefficients that each have a common coefficient value. Applying the convolution operation also includes multiplying the sum by the common coefficient value.