Design and implementation of image kernels using reversible logic gates

Abstract

This study presents the implementation of image kernels used for filtering and enhancing the images using reversible logic gates, a first in reversible logic literature. Image enhancement/filtering is achieved by performing convolution of an image with a filter kernel. This work proposes reversible logic based design and implementation of six filter kernels. The filter kernels implemented are Gaussian blur, Laplacian outline, Sobel, Emboss, Sharpen and Prewitt edge detection. The kernels are implemented individually using reversible logic gates and the designs are measured in terms of quantum cost, garbage outputs, ancilla inputs and gate count. The functional verification is carried out using 512 × 512 standard images on Kintex 7 FPGA platform. The filtered images from the proposed design have an average structural similarity index of 0.92.