A Dual-Kernel Size-Configurable Gaussian Filter Architecture

Image processing applications are crucial for many battery-powered devices that we use every day. These applications require power-efficient architectures to meet power requirements. Gaussian filters are commonly used in image processing applications to enhance images subject to power and quality restrictions. In this work, we propose a dual kernel size configurable Gaussian filter design with hardware shared between the kernels to meet power and quality restrictions without redesigning it. Our design achieves results similar to the standalone kernel architectures with 1 dB improvement for 3×3 kernel. The configurable design reduces the area by 13% and decreases total power up to 52% when operating with the 3×3 mode and 27% for the 5×5 mode, compared to a unified 3×3 and 5×5 kernel design.