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RISS 인기검색어
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- 저자 : Samundiswary Punniyakodi (검색결과 2 건)
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Compression and Enhancement of Medical Images using Opposition Based Harmony Search Algorithm
Rekha Haridoss,Samundiswary Punniyakodi 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.2
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. Overthe years, the transform based and spatial based compression techniques have attracted many types ofresearches 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 failsto 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 withthe optimization algorithm to compress the medical images effectively. However, the method becomes timeconsuming during the measurement of the randomness from the image pixel group and not suitable formedical applications. Hence, an attempt has been made in this paper to develop an HMT based imagecompression by utilizing the opposition based improved harmony search algorithm (OIHSA) as anoptimization technique along with the entropy. Further, the enhancement of the significant informationpresent in the medical images are improved by the proper selection of entropy and the number of thresholdschosen to reconstruct the compressed image.
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Compression and Enhancement of Medical Images Using Opposition Based Harmony Search Algorithm
Haridoss, Rekha,Punniyakodi, Samundiswary Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.2
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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