The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
May. 25, 1993
Filed:
Nov. 08, 1991
Rangarajan Aravind, Matawan, NJ (US);
Hsueh-Ming Hang, Morganville, NJ (US);
Barin G Haskell, Tinton Falls, NJ (US);
Atul Puri, New York, NY (US);
AT&T Bell Laboratories, Murray Hill, NJ (US);
Abstract
A quantization parameter for use in encoding a region of an image is developed from a) a categorization of the region into one of a predetermined plurality of perceptual noise sensitivity (PNS) classes, b) a level of psycho-visual quality that can be achieved for the encoded version of the image, the level being selected from among a plurality of predetermined levels, and c) a prestored empirically derived model of the relationship between the PNS classes, the psycho-visual quality levels and the values of the quantization parameter. PNS indicates the amount of noise that would be tolerable to a viewer of the region, i.e., the perceptual sensitivity of the region to noise. Some characteristics on which PNS classes may be based are: spatial activity, speed of motion, brightness of the region, importance of the region in a particular context, the presence of edges within the region and the texture of the region, e.g., from 'flat' to 'highly textured'. PNS classes that include combinations of the characteristics of a region of the image may also be defined. The PNS classes employed are selected by the implementor and may be determined empirically. The psycho-visual quality of an encoded image is the quality, as perceived by a viewer, of the version of the image that is reconstructed from the encoded image. It is determined from the complexity of the image and the bit-rate available to encode the image.