The Architectural Design of Deblocking Filter for Image Enhancement in the Diagnosis of Cancer

Abstract

Objective:This method is to reduce the risk of imprecise diagnosis associated with poor-quality CT images, this paper presents a new technique designed to enhance the quality of medical CT images. The main objective is to improve the appearance of CT images in order to obtain better visual interpretation and analysis, which is expected to ease the diagnosis process. The proposed technique involves applying a deblocking filter is to enhance the visual nature of a picture by diminishing the blocking artifacts. The appearance of a picture isn’t clear while an antique happens. The proposed deblocking filter calculation gives a strategy to expel the ancient rarities by smoothing the sharp edges of a picture.Methods:With a specific goal to lessen the quantity of information access, multifaceted nature and consequently to upgrade the proficiency, a six-staged pipelined structure for picture pixels are proposed. Besides, to enhance the subjective and target nature of a picture the deblocking filter performs identification of the antique at the coded square limits and weakens them by applying a chose filter.Result:The proposed algorithm is implemented in HDL using Xilinx FPGA. The input image is converted into decimal pixel values using Matlab and this value is used as the input in HDL. The proposed algorithm is compared with other blocking algorithms.Conclusion:To design an effective deblocking filter with low cost, low complexity and high intensity, pipeline based systems are used. In addition to that the number of memory accesses and timing efficiency also be reduced using this method. The deblocking filtering operations can also easily perform in parallel on multiple processors by using six-stage of pipelined, two-line deblocking filter. The parameter mean, variance, standard deviation, resolution, contrast and PSNR values are compared with the previous method. Hence it shows the implementation of deblocking filter using pipelining is more efficient than others.