Many approaches for high-resolution image reconstruction have been proposed in some literatures. One of the most commonly ways is to reconstruct a high-resolution image from a number of rotated and translated images with low resolution. In this process, the exposure difference among original images will decrease the quality of the reconstructed image. In order to remove the influence of the exposure difference, a light energy matching method is proposed in this paper. The theoretical analysis is illustrated in details. Experimental results show that the theoretical analysis is correct and the proposed method is valid.

In avigation, navigation and other fields, electrical image stabilization technique (EIS) is applied widely. Recent research for electrical image stabilization is focused on motion vector estimation, which influences accuracy of image stabilization and its applicable scope directly, and pay less attention to the relation between image stabilization algorithm and structure character of image sensor. In fact, while image sensors are interline transfer CCD, 2D rigid motion model is not accurate enough for the image stabilization algorithm. There exist the displacement between the rows in a frame, for the different rows are exposed at different time. In order to compensate the interline displacement caused by the movement of the sensor both in horizontal and vertical direction, an image revision method based on correlation was put forward for the structure character of interline transfer CCD. During exposure of each frame, the motion of camera is along uniform direction and approximately even (otherwise it is beyond application scope of EIS), so it is feasible to revise image according to the displacement at the top and the bottom of image. Image sequence was acquired by telescope with function of optical image stabilization, and then was processed by electrical image stabilization algorithm. Experiment results showed that the image fidelity has been improved remarkably after image revision processing.

Using pattern recognition to select focus windows, the primary imaging object s which are men (PIOM for short) is discussed in details. The necessity of utilizing pattern recognition in auto2 focus is illust rated. The skin2color dist ribution characteristics are used to detect skin regions in PIOM images. Morphological operations are employed in the process to get ride of interspaces arising f rom eyes, nost rils, mouths and other non2skin part s among skin areas. Then the detected skin regions are chosen as the focus windows. Experimental result s show the realistic applicability and efficiency of this approach.