Design of a radix-4 Booth multiplier with Neighborhood Dependent Approach for video processing applications

In this paper, we propose a neighborhood dependent approach (NDA) for the design of a high performance and low power radix-4 booth multiplier for kernel-based operations such as 2D convolution in video processing applications. The proposed technique reduces dynamic power consumption by analyzing the bit patterns in the input data to reduce switching activities. Special values of the pixels in the video streams such as zero, repeated values or repeated bit combinations are detected and data paths in the architecture design are disabled appropriately to eliminate unnecessary switching in arithmetic units and data buses. Input pixels in the video stream are partitioned into halves to increase the possibility of detecting special values. It is observed that the proposed scheme helps to reduce operations and switching activities in the 2D convolution operations up to 46% of the switching activity rate which results in significant power reduction with low hardware overhead.