A system and method for color correction is disclosed to reduce noise amplification during color correction. The method can comprise color correcting a noise evaluation image using a plurality of color correction parameters, determining a noise amplification metric by comparing the corrected noise evaluation image with the pre-correction noise evaluation image, and adjusting the plurality of color correction parameters based on the noise amplification metric.

In an image processing apparatus, an image acquisition unit acquires an image. A correction unit corrects pixel values of pixels composed of the acquired image by using correction coefficients to produce a correct image. An object recognition unit recognizes an object in the corrected image. A storage unit stores in advance standard color characteristics of a predetermined object which is a recognition target. A color characteristics acquisition unit acquires color characteristics of the predetermined object if the predetermined object is recognized by the object recognition unit. A comparison unit compares the color characteristics of the acquired object with the standard color characteristics of the same predetermined object stored in advance in the storage unit. An updating unit updates the correction coefficients used in the correction unit based on a result of comparison so as to reduce a difference between the color characteristics and the standard color characteristics.

A tone mapping unit applies tone mapping to a block of pixel values. In each of a plurality of iterations, one or more lines of pixel values are processed based on information relating to pixel values of at least one previous line of the block which have been processed in at least one previous iteration. The information is used to determine one or more tone mapping relationships which is/are used to map the pixel values of the current line to tone-mapped pixel values. Furthermore, the information is updated based on the pixel values of the current line and stored for use in processing pixel values of a subsequent line of pixel values of the block in a subsequent iteration.

The processing of RGB image data can be optimized by performing optimization operations on the image data when it is converted into the YCbCr color space. First, a raw RGB color space is converted into a YCbCr color space, and raw RGB image data is converted into YCbCr image data using the YCbCr color space. For each Y-layer of the YCbCr image data, a 2D LUT is generated. The YCbCr image data is converted into optimized CbCr image data using the 2D LUTs, and optimized YCbCr image data is generated by blending CbCr image data corresponding to multiple Y-layers. The optimized YCbCr image data is converted into sRGB image data, and a tone curve is applied to the sRGB image data to produce optimized sRGB image data.

A subject is imaged repeatedly and color images of the subject are obtained. A color histogram is generated from the color subject image obtained and a representative color is decided from the color histogram generated. A specific color range that can be considered a color identical with the representative color is decided from the color histogram and representative color. Color outside the specific color range in the color subject image is changed to gray, an image of the subject in which the non-specific colors have been changed to gray is obtained and the image is displayed. Processing such as deciding the specific color range is repeated. When an instruction to fix the specific color is issued, the specific color range is fixed.

In an image processing apparatus, an image corrector ascertains, for each pixel of a selected pixel region included in an image captured by an imaging unit, luminance-value ratios of respective colors of color filters in accordance with (i) a color luminance value of the corresponding pixel of the selected pixel region, and (ii) ascertainment data items predetermined for the respective colors if a measured illumination level around the imaging unit is lower than or equal to a predetermined threshold illumination level. The ascertainment data item, predetermined for each color, represents a corresponding color luminance-value ratio at any pixel in the selected pixel region with respect to a predetermined peak luminance value of the corresponding color in the selected pixel region. The image corrector generates a corrected image in accordance with the luminance-value ratios of the respective colors ascertained for each pixel of the selected pixel region.

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 lens shading correction circuit includes a gain generator configured to generate a first gain value for each pixel of an input image in response to a gain generation parameter, and an adjustment circuit configured to receive the first gain value and first YUV data, and to adjust at least one of U and V values of the first YUV data using at least one of the first gain value and a Y value of the first YUV data

Provided are an apparatus and a method for generating an image with reduced blown-out highlight regions that represents colors and shades of gray of a subject with high accuracy. The apparatus includes an image processing section that inputs a RAW image corresponding to an output image of an imaging device and performs image processing on the input RAW image. The image processing section performs a demosaicing process, a white-balancing process, and further a pixel value estimation process. The demosaicing process generates RGB images having all pixels set to respective colors of RGB by demosaicing the RAW image. The white-balancing process white-balances the respective RGB images resulting after the demosaicing process. The pixel value estimation process performs a G pixel value estimation process in a saturated pixel region of the G image resulting after the white balancing process. In the pixel value estimation process, the pixel value estimation process is performed by using pixel values of the R and B images resulting after the white balancing process at the same pixel position as the G pixel subject to pixel value estimation.

An image synthesis device includes imaging unit (110) that photographs video, displayer (150) that displays the photographed video, and makeup image superimposing unit (140) that changes brightness of a makeup image superimposed with a face of the video on a pixel basis and superimposes the makeup image of which the brightness is changed on the face of the video, every time skin brightness of the face included in the video changes. Even if the brightness that illuminates the face changes, it is possible to synthesize the makeup image with an image familiar to the skin in real time.