Color filter arrays(CFA) based on complementary colors(CYMG) has been designed and used with the main advantage: higher spectral sensitivity and wider bandwidth than RGB CFA, especially in the low-light or short integration time environment. As for the interline-transfer, interlaced-readout complementary colors CFA pattern CCD, we propose a method of color restoration by the conversion of CYMG-YUV-RGB color space. Specifically, summing horizontally adjacent pixels from raw data can provide estimates of the luminance channel Y, while subtracting horizontally interlaced adjacent pixels can provide estimates of chrominance (color difference) channel U and V individually. A 2 × 2 pixels block of raw data is the smallest cell to figure out Y, U, V channels. Subsequently, transform YUV to RGB linearly according to the conversion formula between CYMG and RGB. At last, the raw data from CCD can be restored to RGB signals which is convenient for post-process, such as white balance. Additionally, we adopt an improved median filter to U and V channels to remove the edge zipper noise caused by interpolation, which can optimize the image quality.
Digital image camera has received more and more attention because of its convenience in storing and transferring, the still exist problems about it are also hot topics of research. Auto white balance is one of the problems, it’s the result of differences between image sensors and human eyes. If the illumination of environment has changed, color cast will happen in image from sensors, but image from eyes due to color constancy won’t. For weakening this inconsistence and acquiring image of same scene under canonical illumination, color adjustment according to color temperature of environment should be considered. In this paper, an auto white balance approach combined gray world and coincidence of chromaticity histogram (GWCCH) is proposed. It’s based on basic assumptions of these two methods, measures color components in image, and selects appropriate routine and arguments to implement auto white balance. In the experiment results, the proposed method can meet the theory of gray world (GW) or coincidence of chromaticity histogram (CCH) respectively, and get good effect in more scenes than these two methods.
Single image super-resolution is one of the most prevalent techniques in digital image processing with a wide range of applications. In this paper, we analyzed the well-known new edge directed interpolation (NEDI) and proposed an improved single image super-resolution method based on edge directed interpolation which could preserve the edge features and reduce common artifacts efficiently. In order to obtain a good tradeoff between quality and speed, a new scheme which moves local window along edge direction is applied. Simulation results demonstrate that the proposed algorithm improves the subjective quality of the interpolated images over the other conventional interpolations with competitive computation complexity.
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