258 results about "Color plane" patented technology

A raw image consists of a plurality of pixels in a plurality of color planes giving a color image. The raw image is split into at least a low frequency image and a high frequency image. At least the low frequency image is color corrected to produce a color corrected low frequency image. The color corrected low frequency image is combined with at least the high frequency image to give a final image which is of comparable resolution to the raw image but is color corrected.

A lossless image encoding / decoding method and apparatus. The lossless color image encoding apparatus includes a motion prediction image generator estimating a motion between a previous image and a current image and outputting a corresponding prediction image, a residue generator generating a temporal residue corresponding to a difference between a prediction image generated by the motion prediction image generator and the corresponding block of the current image with respect to different components of the color image, a prediction residue generator generating prediction residues by defining a linear-transformed value of one residue among the different components of the color image output from the residue generator as a predictor and using differences between each of the residues of the other components and the predictor, and an entropy encoder receiving the residue forming the predictor from the residue generator and the prediction residues from the prediction residue generator and generating a bitstream. Encoding methods, decoding apparatuses, and decoding methods can be implemented similarly.

A system and method is provided for processing a demosaiced image using a color aliasing artifact reduction (CAAR) algorithm in order to reduce color aliasing artifacts. The CAAR algorithm computes the L level wavelet transform for the demosaiced color planes R, G and B. Thereafter, the CAAR algorithm estimates the correct color value at each pixel location for the colors not associated with that pixel location. For example, to determine the green value at red pixel locations, the CAAR algorithm performs an inverse wavelet transform using the green approximation signal and the red detail signals. This process is repeated for each of the colors (e.g., green values at blue pixel locations, red values at green pixel locations, etc.). In addition, the CAAR algorithm performs an inverse wavelet transform on each of the color planes themselves, so that the pixel values of the color associated with each pixel location are not altered. Thereafter, the inverse wavelet transform of each color plane is combined with the inverse wavelet transform of each of the estimated color values for that color plane to produce correlated R, G and B color planes. It is these correlated R, G and B color planes that may later be compressed using a wavelet-based image compression method, such as the JPEG 2000 standard.