The aim of this paper is to enhance the coding performance obtained for images that contain regions without information, here named as no-data regions, within the JPEG2000 framework. In Remote Sensing and in Telemedicine, no-data regions can be produced due to several factors, such as geometric corrections, overlapping of successive layers of information, the interest of the user/application in only certain regions within the image, etc. Most coding systems are not devised to consider such regions separately from the rest of the image, sometimes causing a loss in the coding efficiency. We propose four techniques that address this issue. Experimental results, performed on data from real applications, suggest that the proposed techniques can achieve, in some cases, a PSNR improvement of about 2.5 dB.

No abstract

An important issue of JPEG2000 implementations is the allocation of quality layers, since it determines the optimality of the code-stream in terms of rate-distortion. Common strategies of quality layers allocation use both rate-distortion optimization and rate allocation methods, requiring the user to specify the number of quality layers and a distribution function for their rate allocation. This paper presents a new allocation method of quality layers that, neither needing rate-distortion optimization nor requiring user specifications, constructs a near-optimal code-stream in terms of rate-distortion. Besides, the computational cost of the proposed method is in practice negligible, and its application helps to reduce the computational load of the JPEG2000 encoder.