Abstract
The problem of image optimization, namely the reduction of the physical size of the image by minimizing image quality as little as possible, is considered. The object of research are methods for processing and compressing images. When analyzing the methods, one of the biggest problems was discovered, which consists in the fact that when solving the problem of image processing and compression, the studied methods allow to achieve the slightest loss in quality, but as a result, the compression ratio is significantly reduced. To overcome this problem, it was decided to develop a modification of the JPEG compression algorithm. The proposed modification consists in additional quantization of the spectrum after a discrete cosine transform, and then the resulting spectrum is fed to a Huffman encoder, which makes compression even more efficient. A method is obtained for solving the image optimization problem, which allows one to obtain an image with a smaller size and a large compression ratio while maintaining optimal quality. This is due to the fact that the proposed method has a number of features, as the original color image can have 24 bits per point, in particular, the ability to set the compression ratio. Thanks to this, it is possible to obtain a signal-to-noise ratio of 54.2 dB at a quality factor of zero. Compared with the well-known LZW algorithm, which is much better, as a result of which it allows to get a processed image with a much smaller physical size. The assessment of image quality, depending on the parameters of the task. It is shown that for problems of small and medium dimensions, the developed method provides minimal quality loss. The results of solving the problem for a specific example demonstrate the advantage of the developed method over existing ones. The results can be successfully applied to solve the problem of optimizing image size while maintaining maximum quality
Highlights
Compression and image processing methods have been widely used in various fields of information technology, for example, to increase the speed of loading content on sites with a large number of images
The aim of research is to develop a method for processing and compressing images in order to minimize image size, without significantly affecting image quality
The main stage of the method is the discrete cosine transform (DCT), which is a type of Fourier transform [3]
Summary
Compression and image processing methods have been widely used in various fields of information technology, for example, to increase the speed of loading content on sites with a large number of images. The known methods do not allow to achieve optimal image compression, as they are based on a not quite perfect balance between image quality and size. The urgent task is to develop a modification of the image processing and compression method [1]. The object of research is methods for processing and compressing images. The aim of research is to develop a method for processing and compressing images in order to minimize image size, without significantly affecting image quality
Published Version (Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.