Rekha Haridoss, Samundiswary Punniyakodi, Journal of Information Processing Systems Vol. 15, No. 2, pp. 288-304, Apr. 2019  

https://doi.org/10.3745/JIPS.02.0108
Keywords: Entropy, Harmony Search Algorithm, Image Compression, Multi-Thresholding, Optimization
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Abstract

The growth of telemedicine-based wireless communication for images—magnetic resonance imaging (MRI) and computed tomography (CT)—leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

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