Abstract
Medical image enhancement is an essential process for superior disease diagnosis as well as for detection of pathological lesion accurately. Computed Tomography (CT) is considered a vital medical imaging modality to evaluate numerous diseases such as tumors and vascular lesions. However, speckle noise corrupts the CT images and makes the clinical data analysis ambiguous. Therefore, for accurate diagnosis, medical image enhancement is a must for noise removal and sharp/clear images. In this work, a medical image enhancement algorithm has been proposed using log transform in an optimization framework. In order to achieve optimization, a well-known meta-heuristic algorithm, namely: Cuckoo search (CS) algorithm is used to determine the optimal parameter settings for log transform. The performance of the proposed technique is studied on a low contrast CT image dataset. Besides this, the results clearly show that the CS based approach has superior convergence and fitness values compared to PSO as the CS converge faster that proves the efficacy of the CS based technique. Finally, Image Quality Analysis (IQA) justifies the robustness of the proposed enhancement technique.
Highlights
Image enhancement is one of the protruding research areas in image processing as it is more favorable in numerous applications, namely: military [1], satellite image processing [2], geographical imaging [3] and medical image processing [4]
The brightness of an image are considered in the Logarithmic image processing (LIP) model as the intensity of light that passes through a light filter with absorption function R ( x, y)
The field of medical image enhancement is a significant aspect of medical image processing
Summary
Image enhancement is one of the protruding research areas in image processing as it is more favorable in numerous applications, namely: military [1], satellite image processing [2], geographical imaging [3] and medical image processing [4]. Log transformation is one of the basic well-known image enhancement techniques of the spatial domain that can be efficiently used for dark image contrast enhancements It maps a narrow range of low input gray level values in a broad range of output values [18] [19]. The algorithm must be able to optimize the parameters of the transformation function, based on the input image Such techniques have been proposed for automatic image enhancement [22]. In this study a medical image enhancement algorithm has been proposed using log transform based Cuckoo search (CS) algorithm that optimize its paprameters.
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