JPEG2000 Framework Research Articles

JPEG2000 encoding of images with NODATA regions for remote sensing applications

The aim of this work is to, within the JPEG2000 framework, enhance the coding performance obtained for images that contain regions without useful information, or without information at all, here named as NODATA regions. In Geographic Information Systems (GIS) and in Remote Sensing (RS), NODATA regions arise due to several factors, such as geometric and radiometric corrections, atmospheric events, the overlapping of successive layers of information, etc. Most coding systems are not devised to consider these regions separately from the rest of the image, sometimes causing a loss in the coding efficiency and in the post-processing applications. We propose two approaches that address this issue; the first technique (Average Data Region, ADR) is carried out as simple pre-processing and the second technique (Shape-Adaptive JPEG2000, SA-JPEG2000) modifies the coding system to avoid the regions without information. Experimental results, performed on data from real applications and different scenarios, suggest that the proposed approaches can achieve, e.g., for SA-JPEG2000, a Signal-to- Noise Ratio improvement of about 8 dB. Moreover, in a post-processing application such as a digital classification, the best classification results are obtained when the proposed approaches SA-JPEG2000 and ADR are applied.

JPEG2000 Encoding of Remote Sensing Multispectral Images With No-Data Regions

Most sensors used for remote sensing (RS) purposes capture more than one component to seize different features from the Earth's surface. Usually, either multispectral images acquired for RS applications are corrected or the user/application determines valid regions within the image. Consequently, regions without information may emerge ( no-data regions). This letter proposes to encode multispectral images with no-data regions through the JPEG2000 framework, taking into account the lack of importance of these irrelevant regions. Experimental results, performed on data from real scenarios, suggest that the best approach analyzed is the shape-adaptive (SA) Karhunen-Loe?ve transform to decorrelate the spectral redundancy and then the SA multicomponent JPEG2000. The coding-performance improvement over other coding systems considered (Binary Set Splitting with K-D Trees, SA Wavelet Difference Reduction, and SA TARP) is from 5 to 20 dB in signal-to-noise ratio energy.

Integrating Color Constancy Into JPEG2000

The human visual system is able to perceive colors as approximately constant. This ability is known as color constancy. In contrast, the colors measured by a sensor vary with the type of illuminant used. Color constancy is very important for digital photography and automatic color-based object recognition. In digital photography, this ability is known under the name automatic white balance. A number of algorithms have been developed for color constancy. We review two well-known color constancy algorithms, the gray world assumption and the Retinex algorithm and show how a color constancy algorithm may be integrated into the JPEG2000 framework. Since computer images are usually stored in compressed form anyway, little overhead is required to add color constancy into the processing pipeline.

Robust transmission of regions of interest in JPEG2000

We present a technique to robustly transmit regions of interest in the JPEG2000 framework. The technique assumes a prioritized region of interest coding and optimally assigns channel protection to the coded data according to the importance of every packet in the final bit stream. The mean energy of the transform coefficients contained in a packet, and the distance of a packet from the region of interest, determine the importance of every packet. Channel protection is achieved by means of a concatenation of a cyclic redundancy check outer coder and an inner rate-compatible convolutional coder. Simulation results performed over a Rayleigh-fading channel show an improvement in the visual quality of the reconstructed images.

Exploitation and extension of the region-of-interest coding functionalities in jpeg2000

The purpose of this paper is to present a technique to extend the functionality and the application fields of a spatially selective coding within a JPEG2000 framework. The image quality drop between the regions of interest (ROI) and the background (BG) is considered. From the conventional point of view, the reconstructed image quality steeply drops along the ROI boundary; however this effect can be considered is perceived to be objectionable in some situations. Here we propose a simple quality decay management, which makes use of the concentric ROI with different scaling factors. This allows the technique to be perfectly consistent with the JPEG2000 part 2 ROI definitions and description. The proposed techniques may have a significant impact on applications where both coding rate minimization and coded image quality are important and/or become critical factors. Experiments and examples demonstrate the benefits of the presented approach.

A lifting based system for compression and classification trade off in the JPEG2000 framework

In this paper, we propose a design for a novel lifting based wavelet system that achieves the best trade off between compression and classification performances. The proposed system is based on bi-orthogonal filters and can operate in a scalable compression framework. In the proposed system, the trade off point between compression and classification is determined by the system, however, the user can also fine-tune the relative performance using two controllers (one for compression and one for classification). Extensive simulations have been performed to demonstrate the compression and/or classification performance of our system in the context of the recent image compression standard, namely JPEG2000. Our simulation results show that the lifting based kernels, generated from the proposed system, are capable of achieving superior compression performance compared to the default kernels adopted in the JPEG2000 standard (at a classification rate of 70%). The generated kernels can also achieve a comparable compression quality with the JPEG2000 kernels whilst providing a 99% classification performance. In other words, the proposed lifting based system achieves the best trade off between compression and classification performance at the compressed bit-stream level in the wavelet domain.

Quantisation step selection schemes in JPEG2000

Modified quantisation step selection schemes for the uniform dead-zone scalar quantisation as used in Part I of the JPEG2000 standard are presented. Effects of these quantisation schemes on the lossy compression performance of 5/3 integer wavelet transforms are evaluated. The experiment is carried out in the JPEG2000 framework. Similar consideration may be applied to the real wavelet transforms for lossy image compression.