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.
Influenced by the climatic conditions, such as haze, there exist problems of weak visibility and low contrast for the images and videos captured outdoors. Recently, an effective image haze removal method based on dark channel prior has been proposed. However, the brightness of the result is usually not as bright as the atmospheric light, that makes the whole image looks dim. Besides, the execution speed of this method is slow. As a result, it cannot be applied to the situations with high real-time requirements, such as video streams. In order to solve these problems, an efficient algorithm for image and video dehazing is proposed in this paper. Firstly, the transmission map of hazy image based on the fast fuzzy theory is calculated. Then, according to the statistical principle of dark channel prior and the atmospheric scattering model, the haze-free image under ideal illumination can be restored successfully. Large number of experimental results have shown that, the proposed algorithm can obtain better haze-free results for single image compared with the previous method. More importantly, the execution efficiency has been improved greatly. As a result, video steaming can also be dehazed in real-time so as to meet the occasions with much requirements of industry.
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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