Energy-efficient Gaussian filter for image processing using approximate adder circuits

This paper proposes the use of approximate adder circuits for 3×3 and 5×5 Gaussian filter implementations. The Gaussian filter is a convolution operator which is used to blur images and to remove noise, whose convolution implementation can be designed in hardware using only shifts and addition operations. In this work we evaluate the levels of approximations in computing or loss of accuracy in the arithmetic dataflow that the Gaussian filter can tolerate for a set of eight images. Our work deals with different levels of approximation in Ripple Carry Adders (RCA) which are part of the Gaussian filters adder tree implemented in hardware, and later compared to the best precise implementation of the same filter. Our results show an average energy savings of up to 40% and 25% for the approximate 3×3 and 5×5 Gaussian filters, respectively, without compromising the overall filtered images quality.