In medical research, medical images, e.g., CT scans, MRI, and X-ray images, are the most used images these days. Generally, the term “pixel” is frequently used to point to the elements of a digital image. Each element has its location and value and is known as pixels, images, or picture elements. Indeed, digital images are a particular composition of a limited number of elements. The idea behind digital image processing is the processing of digital images using digital computers. Although traditional medical image analysis techniques have obtained limited success, they cannot deal with colossal image data quantities. A massive number of medical images have been generated with ever-increasing diversity and quality. In the last few years, medical image analysis has been highly developed by enhancing digital imaging methods.
Image processing is a substantial part of medical research/clinical practice. This study helps to better understand these strategies and assists researchers in selecting a more appropriate technique for a given use case. Detailed analysis of the measurement metrics demonstrates better efficiency than the other image processing techniques. PSNR, MSE, and SSIM are three performance metrics that were used for the sample medical images. Finally, the performance metrics were extracted and analyzed based on state-of-the-art methods. These methods were investigated, and several comparison results are demonstrated. Moreover, some enhancing techniques to increase the quality of a compressed image were employed.
So, in this study, two compression techniques, namely lossless compression and lossy compression, were applied for image compression, which preserves the image quality. To reduce the redundancy of the contents of the image, thus increasing the ability to store or transfer information in optimal form, an image processing approach needs to be considered. Thus, for the efficient handling of these extensive data, the compression methods need to be re-explored by considering the algorithm’s complexity. At present, there is an increase in the capacity of data generated and stored in the medical area.
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