qGBbBShift - Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition - page 138

• If ( c i , j & BPmask) > 0, inverse perceptual quantize using Equation (5) (I-ρSQ) with d 1

as viewing distance.
• If ( c i , j & BPmask) = 0, inverse perceptual quantize using Equation (5) (I-ρSQ) with d 2

as viewing distance.

4 Experimental results
The ρGBbBShift method, as the other methods presented here, can be applied to many image
compression algorithms such as JPEG2000 or H i -SET [ 9 ]. We test our method applying it
to H i -SET and the results are contrasted with MaxShift method in JPEG2000 and H i -SET.
The setup parameters are φ = 8 for MaxShift and BPmask = 1111000110110000, d 1 = 5H and
d 2 = 50H, where His picture height (512 pixels) in a 19-in. LCD monitor, for ρGBbBShift. Also,
we use the JJ2000 implementation when an image is compressed by JPEG2000 standard [ 10 ] .

4.1 Application in Well-Known Test Images
Figure 4 shows a comparison among methods MaxShift and GBbBShift applied to JPEG2000,
in addition to, ρGBbBShift applied to H i -SET. The 24-bpp image Barbara is compressed at
0.5 bpp. It can be observed that without visual difference at ROI, the ρGBbBShift method
provide beter image quality at the BG than the general based methods deined in
JPEG2000Part II [ 2 ] .

FIGURE 4 512 × 640 pixel Image Barbara with 24 bpp. ROI is a patch of the image located
at [341 280 442 442], whose size is 1/16 of the image. Decoded images at 0.5 bpp using
MaxShift method in JPEG2000 coder ((a) φ = 8), GBbBShift method in JPEG2000 coder ((b)
BPmask = 1111000110110000), and ρGBbBShift method in H i -SET coder ((c)
BPmask = 1111000110110000). (a) MaxShift in JPEG2000 coder, 0.5 bpp. (b) GBbBShift in
JPEG2000 coder, 0.5 bpp. (c) ρGBbBShift in H i -SET coder, 0.5 bpp.

In order to beter qualify the performance of MaxShift, GBbBShift, and ρGBbBShift methods,
irst, we compared these methods applied to the H i -SET coder and then, we compare MaxShift
and ρGBbBShift methods applied to the JPEG2000 standard and H i -SET, respectively. We com-
press two different grayscale and color images of 1600 , from CSIQ image database [ 11 ] , and
Lenna [ 12 ] at different bit-rates. ROI area is a patch at the center of these images, whose size
is 1/16 of the image. We employ the perceptual quality assessment proposed by Moreno et al.
[ 13 ] called P2SNR, which weights the mainstream PSNR by means of a chromatic induction
model, so we renamed this image quality assessment as C w PSNR.
Figure 5 shows the comparison among MaxShift (Blue Function), GBbBShift (Green Func-
tion), and ρGBbBShift (Red Function) methods applied to H i -SET coder. 512 × 512 pixel Image
1600 both for grayscale and color are employed for this experiment. These figures also show