An image processing device including: a gain value manager for generating white gain values corresponding to a plurality of positions, based on a sensing result of a predetermined white image; a target pixel manager for detecting saturated pixels, based on pixel values received from an external device, and determining target pixels as saturated white pixels of which each have a pixel value that indicates that the saturated white pixel is saturated, based on peripheral pixels of the saturated white pixels among the detected saturated pixels; and a target pixel corrector for changing pixel values of the target pixels, based on the white gain values and pixel values of the peripheral pixels.

A vision system for a vehicle includes a color camera that captures image data, which is processed using an in-line dithering algorithm. The in-line dithering algorithm determines most significant bits and least significant bits of first color data captured by a first photosensing element of a row or column, and the least significant bits of the first color data are added to second color data captured by a second photosensing element of the row or column to generate second adjusted color data. The in-line dithering algorithm determines most significant bits and least significant bits of the second color data, and the least significant bits of the second color data are added to third color data captured by a third photosensing element of the row or column to generate third adjusted color data.

A processing for a first pixel in a picture comprises obtaining a lower limit of a first color component of the first pixel in a first color space based on a distance between a color of the first pixel and a first distorted version of the color in a second color space. An upper limit of the first color component in the first color 5 space is obtained based on a distance between the color and a second distorted version of the color in the second color space. A filtered value is obtained of the first color component and which is equal to or larger than the lower limit and equal to or lower than the upper limit. The processing results in filtered values that are cheaper to encode but that are visibly undistinguishable from the original colors of the pixels.

Because we needed a new color saturation processing in tune with dynamic range transformations necessary for handling the recently introduced high dynamic range image encoding, we describe a color saturation modification apparatus (101) arranged to determine linear color differences (R-Y,G-Y,B-Y) on the basis of an input color (R,G,B) and a luminance (Y) of the input color, and to do a multiplication of the linear color differences (R-Y,G-Y,B-Y) with a gain (g), characterized in that the apparatus is arranged to determine the gain as a function of a difference value (V_in-Y) being defined as the value of the highest one of the linear color differences (R-Y,G-Y,B-Y).

To obtain a color signal having a wide dynamic range (i.e., high sensitivity) and color reproducibility similar to human vision characteristics regardless of the amount of the near infrared components contained in light captured by an imaging device. The imaging device is configured to receive light which has transmitted through the filters selectively transmit light having different wavelengths from each other, to generate an output signal RAW0 by converting the received light using the image pickup element 102 having the plurality of pixels, and to remove, by a removal rate E (Rr) determined in accordance with the ratio Rr of near infrared light component calculated for each pixel, the near infrared light component for each pixel from the generated output signal RAW0, to thereby generate an infrared-separated signal (Ra, Ga, Ba).

The present invention provides a method and apparatus for generating a high dynamic range image (HDRI). After acquiring a first illuminance diagram, a base layer and detail layers are extracted from the first illuminance diagram, where the base layer contains low frequency information of the first illuminance diagram and the detail layers contain high frequency information of the first illuminance diagram. The dynamic range of the base layer is then compressed while dynamic ranges of the detail layers remain uncompressed. Further, a second illuminance diagram is generated from the first illuminance diagram by fusing the base layer with the compressed dynamic range and the detail layers, the second illuminance diagram is mapped onto a plurality of preset color channels; and the images on the plurality of preset color channels are fused into the HDRI. Therefore, the detail information in the original illuminance diagram can be preserved.

An image processing method comprising: receiving a first image signal representing a portion of a captured image with a first dynamic range; generating a second image signal using the first image signal: applying one of: a first gain to the brightness value of each pixel in the portion of the captured image represented by the first image signal having a brightness value less than a first threshold brightness value, the first gain serving to increase the brightness value of each pixel to which it is applied, and a second gain to the brightness value of each pixel in the portion of the captured image represented by the first image signal having a brightness value greater than a second threshold brightness value, the second gain serving to decrease the brightness value of each pixel to which it is applied; and after the application of the one of the first and second gains, performing a conversion process such that the brightness value of each pixel in the portion of the captured image represented by the first image signal becomes represented in the second format, thus forming the second image signal.

Color correction is integrated within global tone mapping operations to modify an image captured using an image capture device. New luminance values are determined for the pixels of the image by performing global tone mapping against those pixels using one or more sets of color correction values, which are applied against respective luminance values and color components of those pixels. The sets of color correction values are identified within 3?3 color correction matrices. A gain curve for modifying contrast values of the image is determined based on at least one of the new luminance values. A modified image is then generated by modifying the contrast values according to the gain curve, for example, by applying a gamma curve against the contrast values using data stored in a three-dimensional lookup table.

In the case where a phenomenon called brightness saturation occurs due to high brightness of light output from a transmission apparatus and high lightness in a portion of a transmitter (light source) within a frame obtained by imaging in a reception apparatus, a decoder in a reception apparatus performs first image processing of shifting the focus by moving a lens in an imager or a filtering process (gradation filtering process) of an image for replacing the color of a brightness saturation area with the color surrounding the brightness saturation area, before determination of a change area, determination of the color of the change area, and decoding of bit string data.

A computer-implemented method for color correction includes obtaining a noise evaluation image by adding noise to a noise-free image, color correcting the noise evaluation image using a plurality of color correction parameters, color correcting the noise-free image using the plurality of color correction parameters, determining a noise amplification metric at least by comparing the corrected noise evaluation image with the corrected noise-free image, and adjusting the plurality of color correction parameters based on the noise amplification metric.