Title :
Vector quantization of images using input-dependent weighted square error distortion
Author_Institution :
Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore, India
fDate :
12/1/1993 12:00:00 AM
Abstract :
The input-dependent weighted-square-error (IDWSE) distortion, which is computationally simple, is shown to offer subjectively better decoded images than the mean-square-error (MSE) distortion. In the presence of image activity, better edge representation is achieved for low-bit-rate VQ image coding without sacrificing anything. This strategy produces an optimal codebook in the IDWSE sense and is therefore preferable to the equivalent subcodebook method. A simple way to compute the image activity is proposed and shown to be quite effective. Introducing block boundary sensitivity in IDWSE distortion produces a decoded image with less blockiness and better edge representation, while the encoder computation is marginally raised
Keywords :
image coding; vector quantisation; IDWSE distortion; block boundary sensitivity; decoded image; edge representation; image activity; input-dependent weighted square error distortion; low-bit-rate VQ image coding; optimal codebook; vector quantization; Circuits and systems; Design optimization; Distortion measurement; Filtering; Humans; Image coding; Performance evaluation; Psychology; Speech coding; Vector quantization;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on