Methods and systems for reconstructing a high frame rate high resolution video in a Bayer domain, when an imaging device is set in a Flexible Sub-Sampled Readout (FSR) mode are described. A method provides the FSR mode, which utilizes a multiparty FSR mechanism to spatially and temporally sample the full frame Bayer data. The multi parity FSR utilizes a zigzag sampling that assists reconstruction of motion compensated artifact free high frame rate high resolution video with full frame size. The method includes reconstructing the high frame rate high resolution video using the plurality of parity fields generated. The reconstruction is based on a FSR reconstruction mechanism that can be a pre-Image Signal Processor (ISP) FSR reconstruction or a post-ISP FSP reconstruction based on bandwidth capacity of an ISP used by the imaging device.

A color temperature of each of a first sensed image that is sensed by a first image sensing device and a second sensed image that is sensed by a second image sensing device different from the first image sensing device is acquired, a color temperature that is common between the first image sensing device and the second image sensing device is decided based on the acquired color temperatures, and color information in an image sensed by the first image sensing device and an image sensed by the second image sensing device is adjusted based on the decided color temperature.

Methods and systems for reconstructing a high frame rate high resolution video in a Bayer domain, when an imaging device is set in a Flexible Sub-Sampled Readout (FSR) mode are described. A method provides the FSR mode, which utilizes a multiparty FSR mechanism to spatially and temporally sample the full frame Bayer data. The multi parity FSR utilizes a zigzag sampling that assists reconstruction of motion compensated artifact free high frame rate high resolution video with full frame size. The method includes reconstructing the high frame rate high resolution video using the plurality of parity fields generated. The reconstruction is based on a FSR reconstruction mechanism that can be a pre-Image Signal Processor (ISP) FSR reconstruction or a post-ISP FSP reconstruction based on bandwidth capacity of an ISP used by the imaging device.

A pixel array including; color filter array (CFA) cells, each respectively including CFA blocks, each CFA block including color pixels, and the color pixels include a sub-block. The sub-block includes at least one first color pixel sensing a first color, at least one second color pixel sensing a second color different from the first color, and at least one third color pixel sensing a third color different from the first color and the second color.

A first group of interpolation calculators performing interpolation by mean preserving interpolation calculation, and a second group of interpolation calculators performing interpolation by interpolation other than the mean preserving interpolation calculation are provided. Each of the interpolation calculators performs interpolation calculation for the missing pixel to calculate an interpolation candidate value (M(h)), and calculates test interpolation values (M(t)) treating pixels in a vicinity of the missing pixel as test pixels. A decider (4) selects one of the plurality of interpolation calculators based on results of the test interpolation. An outputter (5) selects the interpolation candidate value outputted from the interpolation calculator selected by the decider (4), among the plurality of interpolation candidate values (M(h)), and outputs the selected interpolation candidate value. Interpolation can be performed such that the interpolated pixel does not look unnatural, and yet the storage capacity and the data processing amount that are required are relatively small.

There is provided with an image processing apparatus. A noise reduction unit generates a noise-reduced image in which noise is reduced from an input image in which a plurality of types of pixels that represent mutually different types of color information are arranged in one plane. An extraction unit generates a high-frequency emphasized image in which a high-frequency component of the input image is emphasized. A demosaicing unit generates a demosaiced image having a plurality of planes that each represent one type of color information by demosaicing processing to the noise-reduced image. A generation unit generates an output image by correcting the demosaiced image by using the high-frequency emphasized image.

A system accesses an image with each pixel of the image having luminance values each representative of a color component of the pixel. The system generates a first histogram for aggregate luminance values of the image, and accesses a target histogram for the image representative of a desired global image contrast. The system computes a transfer function based on the first histogram and the target histogram such that when the transfer function is applied, a histogram of the modified aggregate luminance values is within a threshold similarity of the target histogram. The system modifies the image by applying the transfer function to the luminance values of the image to produce a tone mapped image, and outputs the modified image.

Processing raw image data in a camera includes computing a luminance image from the raw image data, and computing a chrominance image corresponding to at least one of the sensor's image colors from the raw image data. The luminance image and chrominance image(s) can represent the same range of colors able to be represented in the raw image data. The chrominance image can have a lower resolution than that of the luminance image. A camera for performing the method is also disclosed.

A Bayer-mask image is decoded by forming a decoded green array; calculating a slope at each pixel of the array, expressed as an angle; calculating an activity at each pixel; converting the slope angle and the activity into a complex number for each pixel, of modulus equal to the activity and argument equal to twice the slope angle; expressing said complex numbers in Cartesian coordinates to form a Cartesian slope signal and filtering the Cartesian slope signal with a linear spatial filter to derive a slope measure. Blue-green and red-green values are calculated and interpolated using a slope-adaptive interpolation filter steered by said slope measure.

A method for reconstructing a colour image acquired by a photosensitive sensor covered with a mosaic of filters of different colours making up a base pattern, obtaining the product of a demosaicing matrix with a matrix representation of a mosaic image coming from the sensor following acquisition of the colour image by the sensor, the product of the demosaicing matrix with the matrix representation of the mosaic image performing an interpolation of the colour of each pixel of the mosaic image as a function of a pixel neighbourhood of a base pattern corresponding to the base pattern of the mosaic of filters.