Abstract
Remote sensing, environmental monitoring, pattern recognition, and other fields all use this critical and indispensable basic technology. The article proposes an image contrast enhancement detection algorithm based on a linear model to address the problem that the current global contrast enhancement detection algorithm does not have high classification accuracy under the low-intensity JPEG compression quality factor. To decompose the original image, use the biorthogonal wavelet transform. The improved fuzzy set enhancement algorithm is used for the low-frequency subband coefficient. The results obtained after simulating this algorithm show that it is very effective in improving contrast, enhancing image details, and suppressing noise. It has the ability to greatly improve the image’s visual effect, as well as the advantages of parameter adaptation and high algorithm efficiency.
Highlights
Image cooling has become an indispensable component of its optimization, with applications in remote sensing, environmental monitoring, pattern recognition, and a variety of other fields [1]. e study of classical constrained mechanical systems is the focus of analytical dynamics
In the process of image collection and transmission, it is susceptible to the influence of external environmental factors, such as light intensity, transmission medium, and imaging system, which cause image quality to Wireless Communications and Mobile Computing decline [6]. e image formed on the camera image surface by the space observation image is typically low in contrast, the gray level distribution in the histogram is concentrated, and the target is submerged in the complex background. e image needs to be enhanced in order to improve the visual effect and image quality
Some effective new methods and theories have been proposed in recent years. e image should be improved. e image quality is improved, the visual effect of the image is improved, the required information is highlighted, the amount of image data is compressed, and preprocessing work is completed for further image analysis and interpretation using image enhancement technology [7]. e goal of the histogram grayscale transformation is to change the dynamic range of the image grayscale by modifying the grayscale of the input image and each pixel one by one according to certain rules
Summary
Image cooling has become an indispensable component of its optimization, with applications in remote sensing, environmental monitoring, pattern recognition, and a variety of other fields [1]. e study of classical constrained mechanical systems is the focus of analytical dynamics. Nonlinear diffusion equations and fast explicit diffusion methods are used to construct the space in the improved SIFT remote sensing image registration algorithm based on nonlinear scale space. It has the advantage of preserving the scale space image. E method used in this paper to distinguish contrastenhanced images is an image contrast enhancement forensics technology based on linear models. It can effectively classify images and resist JPEG compression
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