NEDA: a low-power high-performance DCT architecture

A VLSI implementation of a new simultaneous images compression and encryption method

“…The authors of [13] use Distributed Arithmetic (DA) multipliers and show that N-point DCT can be obtained by computing N N/2-point inner products instead of computing N N-point inner products. In [14], a new DA architecture called NEDA is proposed, aimed at reducing the cost metrics of power and area while maintaining high speed and accuracy in digital signal processing (DSP) applications. Mathematical analysis proves that DA can implement inner product of vectors in the form of two's complement numbers using only additions, followed by a small number of shifts at the final stage.…”

“…Comparative studies show that NEDA outperforms widely used approaches such as In this paper, we will not optimize the arithmetic operators but we present a new algorithm based on Loeffler one and makes dependency between the compression ratio and the material complexity. Consequently, optimizations in [12], [13] or [14] can be used with the presented new algorithm.…”

Low-power multiplierless DCT for image/video coders

“…For 2-D DCT, the rowcolumn decomposition technique can be used [1]. It reduces the complexity of DCT by a factor of four.…”

“…In most of the 2-D DCT implementations for image/video coders, 12-bit precision has been used in order to conform to IEEE 1180-1990 accuracy specifications [1][2] [10]. Unsigned 11-bit expressions of the cosine coefficients for the 8×1 DCT are shown in Table I.…”

“…Its computational burden is due to large numbers of multiplications and additions. Multiplierless architectures, such as distributed arithmetic (DA), new DA (NEDA), coordinate rotation digital computer (CORDIC) and integer DCT (intDCT), are widely used for its VLSI realization because of improvements in speed, area overhead and power consumption [1]- [4]. These advantages of multiplierless architectures are due to multiple constant multiplications using optimized shift-and-add operations instead of generic arraymultipliers.…”