Aerial images had been used in various fields. If the shooting it in conditions of bad weather, that quality was damage. So requires use of image processing methods for improvement. With the growth and progress of technology, image enhancement method is quickly flourishing. That needs of different options for the appropriate treatment. In this study, image enhancement by the nature of Bi-dimensional empirical mode decomposition (BEMD). Empirical mode decomposition in nonlinear signal processing has excellent results. It can break out some of the base signal and trend. In the BEMD of the signal information for the edge of the image, the trend term for the light distribution. Decomposition can be retained the edge features of the image, and contrast of light and shadow maps make adjustments to improve the uneven lighting situations. In order to retain the color information, so the decomposition of the image before the image for color conversion, will be divided into three¡@degrees of brightness and color images, and then the brightness of the image for the¡@decomposition of the action. The use of subjective and objective image evaluation indicators, to determine the two-dimensional empirical mode decomposition¡@ method with other image enhancement difference. The results show that the conventional image enhancement has a problem that bright side of the whole image, resulting in reduced edge feature information. However, BEMD to effectively improve the image problem of uneven brightness and thoroughly to keep edge features.

This master's thesis deals with lossless video compression. This thesis includes basic concepts and techniques used in image representation. The reader can find an explanation of basic difference between lossless video compression and lossy video compression and lossless video compression limitations. There is also possible find a description of the basic blocks forming the video codec (every block is described in detail). In every block there are introduced its possible variants. Implemented lossless videocodec was compared with common lossless videocodecs.