Design of Image Kernels using Reversible Logic Gates: Enhancing Image with Information-Preserving Operations

This research study demonstrates the design of several image kernels and reversible logic gates to carry out various functions such as enhancement, blurring, sharpening, and embossing of a greyscale image whereas image kernels are used in the convolution process. These six filter kernels are designed using the reversible logic gates, and the image kernel metrics are measured in terms of Gate count, Ancilla inputs, Garbage outputs, and Quantum cost. These metrics of each kernel are calculated to analyze the performance of a kernel. These pixel values are convoluted with respect to different image kernels. MA TLAB tool is used for extracting the pixel values of a greyscale images and the Xilinx Vivado tool is for design implementation and functionality Verification.