In this paper, the approach of changing bit depth of images is considered. This type of operation is required when performing primary processing operations, identifying parameters and stitching images. The process of changing bits depth of images is performed in three stages. At each stage, the error minimization criterion is tested Result of applying the approach allows obtaining numerical region characteristics including the number of clusters, the number of minimum and maximum cluster sizes. To perform the process of minimizing some of the criteria, it is necessary to divide the image into areas. The paper presents a mathematical description of the approach, as well as flowcharts for performing operations of data processing steps. The article gives recommendations for choosing coefficients to obtain optimal minimizing parameters. The test images give an example of performing bit changes on image areas.

Images captured in surveillance systems suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. We present a new image enhancement algorithm based on multi-scale block-rooting processing. The basic idea is to apply the frequency domain image enhancement approach for different image block scales. The parameter of transform coefficient enhancement for every block is driven through optimization of measure of enhancement. The main idea is that enhancing the contrast of an image would create more high-frequency content in the enhanced image than the original image. To test the performance of the proposed algorithm, the public database O-HAZE is used.

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