Low bit depth representation motion estimation algorithms: a comparative study

Abstract

A comparative study of low complexity motion estimation algorithms is presented. The algorithms included in the study are the 1-bit transform, the 2-bit transform, the constrained 1-bit transform and the multiplication free 1-bit transform which are using different motion estimation strategies compared to standard exhaustive search algorithm-mean absolute difference or similar combinations. These techniques provide better performance in terms of computational load compared to traditional algorithms. Although the accuracy of motion compensation is only slightly lower comparing to the other techniques, results in terms of objective quality (peak signal-to-noise ratio) and entropy are comparable. This fact, nominates them as suitable candidates for inclusion in embedded devices applications where lower complexity translates to lower power consumption and consequently improved device autonomy.

Block-based motion estimation algorithms — a survey

“…92, motion−compensated PSNR obtained with full eight−bit pixel resolution is compared with results for 1BT and 2−bit transform (2BT) [51]. Five CIF video se− quences were used in the experiments ("Coastguard", "Mo− bile calendar", "Football", "Flower garden", and "Bowing") with SR set to ±8 pixels.…”

Reduced bit low power VLSI architectures for motion estimation

“…a 4-bit ripple adder is as fast as a carry select or carry save adder but is smaller), and the reduced bit SAD (RBSAD) calculations are faster and consume less power. The memory will be smaller as well as the input/output (I/O) memory bandwidth [3,[11][12][13][21][22][23][24][25]. A drawback [21][22][23] of this method which was pointed out previously is that the reduced dynamic range, from 8-bit numbers to 4-bit numbers, will generate poorer peak signal to noise ratio (PSNR) values especially for sequences with high spatial and temporal correlations (e.g.…”

“…newscaster kind of sequences) through an increased error metric and consequently will require a greater bit rate. In [24,25] low bit depth ME algorithms for low power and their hardware architectures were presented. Work in [26][27][28] showed the use of adaptive quantization in the MPEG-2 encoder, for low power and compensating for the quality loss due to 4-bit/pixel on the average.…”