Abstract
Block truncation coding (BTC) is commonly used to compress a
video to be stored in frame memory for display devices such as LCDs.
The original BTC algorithm partitions an input image into 4
$\times$
4
blocks and compresses each block to reduce the data size down to 1/4
of the original size of the data. As the size of a video displayed
on an LCD increases, the frame memory size also increases. Therefore,
it is necessary to reduce the frame memory size further. The previous
BTC suffers from a severe quality degradation when its compression
ratio exceeds 6 to the original data. This paper proposes a novel
BTC-based compression algorithm of which the target compression ratio
is 12. To improve the compression efficiency, the proposed algorithm
adopts a bit-saving scheme that utilizes the spatial correlation between
vertically adjacent blocks. Furthermore, the blocks with low image
complexity are coded using one 2
$\times$
16 coding block while those
with high image complexity are coded using two 2
$\times$
8
coding blocks. With the hardware implementation for a high throughput
constraint, the memory sizes of the encoder and decoder are 21,312
bits and 5952 bits, respectively, whereas the gate counts of the encoder
and decoder are 68.7 K and 13.6 K, respectively. Experimental results
show that the average PSNR of the proposed algorithm is 30.03 dB and
that the throughputs of the encoder and decoder are 27.5 Gbps and
63.9 Gbps at operating frequencies of 143 and 333 MHz, respectively.
© 2015 IEEE
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