Multiple color channel multiple regression predictor

摘要

Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and crosspixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

主权项

1. A method to approximate using a processor an image having a first dynamic range in terms of an image having a second dynamic range, the method comprising;
receiving a first image and a second image, wherein the second image has a different dynamic range than the first image; selecting a multi-channel, multiple-regression (MMR) prediction model from one or more MMR models; determining values of prediction parameters of the selected MMR model; computing an output image approximating the first image based on the second image and the determined values of the prediction parameters of the selected MMR prediction model, wherein pixel values of at least one color component in the output image are computed based on pixel values of at least two color components in the second image; and outputting the determined values of the prediction parameters and the computed output image wherein selecting the MMR prediction model from the one or more MMR prediction models further comprises an iterative selection process comprising: (a) selecting and applying an initial MMR prediction model; (b) computing a residual error between the first image and the output image; (c) selecting the initial MMR model if the residual error is smaller than an error threshold and no further MMR prediction model is selectable; otherwise,selecting a new MMR prediction model from the variety of MMR prediction models, the new MMR prediction model being different from the previously selected MMR prediction model; and returning to step (b).