A Novel Image Processing Approach to Enhancement and Compression of X-ray Images

有损压缩 无损压缩 计算机科学 图像压缩 冗余(工程) 数据压缩 图像处理 人工智能 图像质量 纹理压缩 计算机视觉 压缩(物理) 图像(数学) 数据挖掘 材料科学 复合材料 操作系统
作者
Yaghoub Pourasad,Fausto Cavallaro
出处
期刊:International Journal of Environmental Research and Public Health [Multidisciplinary Digital Publishing Institute]
卷期号:18 (13): 6724-6724 被引量:25
标识
DOI:10.3390/ijerph18136724
摘要

At present, there is an increase in the capacity of data generated and stored in the medical area. Thus, for the efficient handling of these extensive data, the compression methods need to be re-explored by considering the algorithm’s complexity. 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. So, in this study, two compression techniques, namely lossless compression and lossy compression, were applied for image compression, which preserves the image quality. Moreover, some enhancing techniques to increase the quality of a compressed image were employed. These methods were investigated, and several comparison results are demonstrated. Finally, the performance metrics were extracted and analyzed based on state-of-the-art methods. PSNR, MSE, and SSIM are three performance metrics that were used for the sample medical images. Detailed analysis of the measurement metrics demonstrates better efficiency than the other image processing techniques. This study helps to better understand these strategies and assists researchers in selecting a more appropriate technique for a given use case.
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