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Edge based enhancement of retinal images using an efficient JPEG- compressed domain technique

机译:基于EDGE的使用高效JPEG-压缩域技术的视网膜图像增强

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摘要

With substantial usage of Imaging Technology in the medical field for the diagnosis and treatment of illnesses, a huge volume of medical images are being generated which provide a bigger challenge in terms of storage, transmission and processing. The high resolution medical images thus generated occupy large storage space, and hence they are subjected to compression to make them storage and transmission efficient. Though compression overcomes the issues of storage and transmission to some extent, but the problem of processing compressed images still remains as a challenge. This is because; the usual way of processing the compressed medical images is through the operations of decompression and recompression, which consume lots of computing resources. Therefore, it would be novel, if the compressed medical images are processed and analysed directly in the compressed formats without involving the expensive operations like decompression and recompression. In this direction, the current research paper demonstrates a novel technique of edge based enhancement of retinal images, which is a very critical operation from disease diagnosis perspective, directly in the JPEG compressed domain. The developed algorithm is validated with publicly available retinal datasets of DRIVE and DIARETDB1, and the performance reported is compared with the state-of-the-art techniques in the uncompressed (spatial) domain in terms of both quality of enhancement and computation time.
机译:在疾病诊断和治疗的医学领域进行了大量的成像技术,正在产生大量的医学图像,这在储存,传输和处理方面提供了更大的挑战。如此生成的高分辨率医学图像占据了大存储空间,因此它们受到压缩以使其存储和传输效率。虽然压缩在某种程度上克服了存储和传输的问题,但处理压缩图像的问题仍然是挑战。这是因为;处理压缩的医学图像的通常方法是通过减压和再压缩的操作,这消耗了许多计算资源。因此,如果压缩的医学图像直接以压缩格式直接处理并分析,则这将是新颖的,而不涉及昂贵的操作等解压缩和再压缩。朝着这个方向,目前的研究论文证明了一种基于视网膜图像的边缘增强的新技术,这是一种非常关键的疾病诊断视角的操作,直接在JPEG压缩域中。发达的算法验证了驱动器和DiaRetdB1的公开视网膜数据集,并将报告的性能与未压缩(空间)域中的最新技术进行比较,而不是增强和计算时间的质量。

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