Tone deviation evaluation of boundary pixels static raster image using balanced extending algorithms

While use algorithms of pre-processing raster image involves improving image characteristics to use qualitative transformation effect result on following processing stages. Assessing the effect of an impact on a raster image is not a trivial task, where the choice of further processing steps and algorithmic tools depends on the quality of its implementation. The algorithm for balanced "extension" of boundary pixels of a static raster image is as example. Algorithm developed to improve the results of object edge detection algorithms based on the two-dimensional convolution operation, where the improvement consists of reducing the number of sharply contrasting pixels at the boundaries of raster images relative to adjacent ones. Existing numerical raster images estimates of PSNR and SSIM which obtained after applying the balanced algorithm of redefining border pixels have shown their low efficiency due to the small number of pixels affected by the transformations. The tonal deviation of raster image boundary pixels is alternative assessment criterion. The object of study in the article is the pixel matrix of three-channel color static raster image. The subject of the study is the evaluation of the tonal deviation of the boundary pixels of a static raster image obtained by used balanced algorithm for redefining border pixels. The main objective is to calculate the tonal deviation estimates of boundary static raster images after applying balanced algorithm of "redefining" border pixels, analysis and ranking by alternative methods of "extension" of boundary sizes according to the criterion of tonal deviation. The article provides a definition of the concept of tonal deviation and justification for the use of tonal deviation assessment. An example of calculating the tonal deviation of pixels after applying the balanced algorithm of "redefining" border pixels and the copy method for 1 thousand color three-channel raster images from the SpaceNet Satellite Images dataset from ImageNet is presented. It was carried out short analysis of the obtained assessment results and recommendations for choosing the best methods of "redefining" border pixels.

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