No abstract

This paper proposed an automatic exposure algorithm based on luminance histogram and region segmentation. The method ensures well exposure to the main object under the backlighting or excessive front-lighting conditions, and uses the characteristics of the luminance histogram to judge the scene condition. According to the luminance histogram, if the image under normal light conditions, the method compares the average luminance value of the image with the corresponding reference target brightness value to adjust exposure compensation. If the image under special conditions, the average brightness value will be calculated using fixed-partition method and exposure compensation will be adjusted. The paper combines auto-exposure and auto-gain control to adjust the exposure compensation. As it turns out, this method in a variety of light conditions can achieve well exposure.

With the continuous development of computer and network technology, people's life has been inseparable from the Internet. Consequently, Internet users rapid grow, online shopping boom, clothing industry e-commerce rapid rise, change pattern of garment industry, at the same time, the proportion keeps increasing. Through careful analyses of the data from China E-business Research Center and iResearch net, this paper researches development trend of e-commerce and clothing commerce, describes the problems existing in China clothing brand e-commerce at the present stage, further, explore new e-commerce marketing mode: O2O, studies and elaborates the operation and promotion method of Chinese clothing brand e-commerce O2O mode.

This paper presents the structure and the operational principle of CMOS image sensors. And then the reason is illuminated for producing dark current and black level of CMOS image sensors. It is necessary to calibrate dark current and black level to improve quality of CMOS image sensors. The dark current is corrected by optimizing pixel structure, perfecting technology, improving 6layout, and correction double sample. But these ways do not calibrate black level. So, it is important to calibrate black level using black level calibration algorithm in the stage of image processing.