Most image processing applications are naturally imprecise and can tolerate computational error up to a specific limit. In such applications, savings in power are achieved by pruning the data path units, such as an adder module. Truncation, however, may lead to errors in computing, and therefore, it is always a challenge between the amount of error that can be tolerated in an application and savings achieved in area, power and delay. This paper proposes a segmented approximate adder to reduce the computation complexity in error-resilient image processing applications. The sub-carry generator aids in achieving a faster design while carry speculation method employed improves the accuracy. Synthesis results indicate a reduced die-area up to 36.6%, improvement in delay up to 62.9%, and reduction in power consumption up to 34.1% compared to similar work published previously. Finally, the proposed adder is evaluated by using image smoothing and sharpening techniques. Simulations carried out on these applications prove that the proposed adder obtains better peak signal-to-noise ratio than those available in the literature.
Power efficient scheduling over fading channel for cross-layer optimization
