A circuitry for image demosaicing and enhancement and an image-processing method thereof are provided. The circuitry includes a storage device that is used to temporarily store an image and is jointly used by circuits that perform color restoration and brightness reconstruction. The circuitry includes a color restoration circuit for performing image interpolation and a global mapping circuit that performs mapping to obtain brightness of an image according to restored red, green and blue information of every pixel. Further, an edge texture feature decision circuit is provided to obtain each pixel's directionality for color restoration. A brightness estimation circuit utilizes green information of the pixels as the brightness for an area. After that, a color image with the color restoration and brightness reconstruction is outputted.

Methods, systems, and devices for image processing are described. A device may capture image data based on a color filter array (CFA) associated with an image sensor. The image data may include a set of pixels. The device may determine a CFA pattern of the CFA and select a configuration appropriately. The configuration may include an indication of a first set of neighboring pixels for each pixel of the set of pixels to use to determine that a pixel is defective and a second set of neighboring pixels for each pixel of the set of pixels to use to correct the defective pixel. The device may determine that the pixel of the set of pixels is defective using the configuration, and correct the defective pixel using pixel values of the first set of neighboring pixels, or pixel values of the second set of neighboring pixels, or both.

The invention relates to the processing operation of interpolating the colours of a Bayer mosaic image sensor. A first elementary matrix filter, which is a bilinear interpolation filter, of size mm, m being an odd number larger than or equal to 3, a low-pass matrix filter of size nn, n being an odd number larger than or equal to 3, and a high-pass matrix filter, complementary to the low-pass filter, of size nn, are defined. The first matrix filter is convoluted with the low-pass filter, resulting in a low-frequency interpolation filter of size (m+n1)(m+n1), and the first matrix filter is convoluted with the high-pass filter, resulting in a high-frequency interpolation filter of size (m+n1)(m+n1). The matrix of digital signals arising from the pixels is filtered separately, using the pixels of each colour, by the low-frequency interpolation filter. The complete matrix of signals is filtered using the high-frequency interpolation filter. The result of the low-frequency filtering operation and the result of the high-frequency filtering operation are added together, for each pixel, in order to obtain a numerical value of a given colour of that pixel.

Methods, systems, and devices for processing color information are described. The method may include receiving a first set of image data collected at an image sensor based on a first color filter array having a first filter pattern, calculating a color saturation gradient based on the first set of image data, and calculating multiple color gradients based on the color saturation gradient. The multiple color gradients may each be associated with a region of the first set of image data, where each color gradient characterizes a color variation along a different direction of the region. The method may include generating a second set of image data including a color value for the region based on comparing a first direction gradient of the multiple color gradients with a second direction gradient of the multiple color gradients. Color values associated with the regions may be mapped to a second color filter array.

A device (e.g., an image sensor, camera, etc.) may identify a camera lens and color filter array (CFA) sensor used to capture an image, and may determine filter parameters (e.g., a convolutional operator) based on the identified camera lens and CFA sensor. For example, a set of kernels (e.g., including a set of horizontal filters and a set of vertical filters) may be determined based on properties of a given lens and/or q-channel CFA sensor. Each kernel or filter may correspond to a row of a convolutional operator (e.g., of a restoration bit matrix) used by an image signal processor (ISP) of the device for non-linear filtering of the captured image. The corresponding outputs from the horizontal and vertical filters (e.g., two outputs of the horizontal and vertical filters corresponding to an input channel associated with the CFA sensor) may then be combined using a non-linear classification operation.

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.

A method of de-mosaicing pixel data from an image processor includes generating a pixel block that includes a plurality of image pixels. The method also includes determining a first image gradient between a first set of pixels of the pixel block and a second image gradient between a second set of pixels of the pixel block. The method also includes determining a first adaptive threshold value based on intensity of a third set of pixels of the pixel block. The pixels of the third set of pixels are adjacent to one another. The method also includes filtering the pixel block in a vertical, horizontal, or neutral direction based on the first and second image gradients and the first adaptive threshold value utilizing a plurality of FIR filters to generate a plurality of component images.

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.

In an optical system, a color filter mosaic can determine first color pixel locations, second color pixel locations, and third color pixel locations in an array of sensor pixels. The optical system can capture overhead images, which can be subtracted to form a background-subtracted tri-color image of a reflection of sunlight from at least one ground-based curved mirror. A processor can scale color values at the first and second color pixel locations of the tri-color background-subtracted image. The processor can form a single-color background-subtracted image from the scaled color values at the first color pixel locations, the scaled color values at the second color pixel locations, and third color values at the third color pixel locations. The single-color background-subtracted image can correspond to a point spread function or a line spread function of the optical system.

A method of adaptive demosaicing of a mosaiced image includes receiving the mosaiced image having a mosaic pattern with a first color, a second color, and a third color, obtaining a noise level index for the mosaiced image, determining whether the noise level index is greater than a threshold value, and, in response to the noise level index being greater than the threshold value, performing an adaptive demosaicing on the mosaiced image to generate an adaptively demosaiced image. The adaptive demosaicing includes interpolating values of a portion of unknown pixels of the first color in a horizontal or vertical direction, interpolating values of a portion of unknown pixels of the second color in a horizontal or vertical direction, and interpolating values of a portion of unknown pixels of the third color in a horizontal or vertical direction.