Kenji Sugiyama

© 2020 IEEE. It is common in color imaging to use a single-sensor system with a color filter array (CFA), especially a Bayer CFA. Recently, color filter methods using the white component have been studied to improve both resolution and sensitivity. However, de-mosaicking performance is improved using a correlation of color planes, especially for a Bayer CFA. We propose a new imaging system with a pastel-color CFA. In this system, the color plane reconstruction is realized with an abstraction of the white-like component from RAW images. To improve performance, we discuss the use of the highfrequency component. However, the effect of sensor noise on the imaging performance has not been closely investigated in such imaging systems. In this paper, we evaluate these effects on various imaging systems. In our experiment, the optical color filter and sensor noise are simulated using computer calculations. With these results, it is recognized that the proposed method is less affected by sensor noise.

Currently, Y, Cb, Cr 4:2:0 system is widely used as the color format for the video system. We have proposed the frame sequential system as an alternative method which has one color plane in a frame. In this system, the conversion to usual RGB requires a motion compensated color interpolation. However, it is not easy in the case of high saturation color images, because of its difference between color planes. To avoid this problem, we propose the new color format which has dependent colors. The primary colors (RGB) are changed to pastel colors. The conversion from RGB to pastel colors is realized by the color matrix. Re-conversion is also possible by using the inverse matrix. To address the conversion to RGB, basic block matching is used in motion estimation. To avoid incorrect motion vectors, the antierror mechanism are strengthened. Finally, the performance of the pastel colored frame sequential and 4:2:0 are compared. From experimental results, the converted RGB pictures have higher PSNR than 4:2:0.

Very high-resolution video systems, such as 4K (3840x2160), enable a very close viewing distance that is almost the same as the picture height. This technology enables high-reality systems in homes to be realized. However, the very short distance causes significantly different views across the picture, and uniform processing for the picture may not always be the best choice. Here, we calculate the actual view size of a pixel, which depends on the pixel position in close viewing. We proposed the perceptual coding methods using pre/post-processing for the picture to be coded. It is a quantization control by a contrast change. However, the control of quantization should be decided based on the perceptual performance between pixel size and quantization. Therefore, we carried out subjective assessment about this. The bit rate reduction is checked for each method. The 4K resolution processing is realized by four patterns of HDTV picture coding with AVC. As the results of these experiments, it is recognized that the bit rate reduction 15 percent by the optimal coding.