Compression and Enhancement of Medical Images using Opposition Based Harmony Search Algorithm
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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.
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. 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.
참고문헌 (34)
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