3:30, IMDSP-P1.1
ROBUST PACKET IMAGE TRANSMISSION BY WAVELET COEFFICIENT DISPERSEMENT
T. FRAJKA, K. ZEGER
We present a packetization method for robust image transmission over packet erasure channels. The packets are formed in such a way that the image information is spread over different frequency bands and spatial locations to avoid complete disruption of certain image blocks in case of a packet loss. Experimental results are provided to demonstrate the performance of this method.

3:30, IMDSP-P1.2
A BIORTHOGONAL TRANSFORM WITH OVERLAPPING AND NON-OVERLAPPING BASIS FUNCTIONS FOR IMAGE CODING
T. TANAKA, Y. YAMASHITA
This paper presents a new framework for a biorthogonal lapped transform that consists of long and short basis functions called the VLLBT. It is shown that when the biorthogonal long basis functions of the VLLBT are given, the optimal short basis functions in the energy compaction sense are derived by solving an eigenvalue problem without iterative searching techniques. We also provide design and image coding examples of the VLLBT. The resulting VLLBT attains high coding gain comparing to other lapped transforms. Moreover, experimental results show that the proposed VLLBT is superior to other conventional transforms in terms of PSNR at high compression ratio. Furthermore, it significantly reduces the annoying blocking artifacts.

3:30, IMDSP-P1.3
A WAVELET-TREE IMAGE CODING SYSTEM WITH EFFICIENT MEMORY UTILIZATION
Y. ANDREOPOULOS, P. SCHELKENS, N. ZERVAS, T. STOURAITIS, C. GOUTIS, J. CORNELIS
This paper describes an efficient implementation of an image coding system based on the independent wavelet-tree coding concept. The system consists of a transform and a (de)coding engine that operate in a pipelined fashion. The main focus of this paper will be on the encoding part since, due to the system architecture, the decoder has identical memory utilization. Experimental results prove that the proposed system achieves comparable coding performance to the state-of-the-art, while it localizes the memory accesses to small memory modules and uses minimal computational resources.

3:30, IMDSP-P1.4
LINEAR-TRANSLATE CONSTRAINED STORAGE VQ FOR VSPIHT WAVELET IMAGE CODING
D. MUKHERJEE, S. MITRA
A new Constrained Storage VQ (CSVQ) structure based on linear transforms and translates of a common root codebook is proposed. The new VQ structure, named LT-CSVQ (Linear Translate CSVQ), acts as a building block for multistage VQ implementations (LT-CS-MSVQ), and significantly reduces storage requirements from that required in tree-multistage VQ implementations. LT-CS-MSVQ is most appropriate for medium rate multistage VQ implementations, and is applied to the recently proposed vector enhancement of Said and Pearlman’s Set Partitioning in Hierarchical Trees (SPIHT) image coder, named VSPIHT.

3:30, IMDSP-P1.5
CLOSED LOOP OPTIMIZATION OF IMAGE CODING USING SUBJECTIVE ERROR CRITERIA
M. ETOH, M. KOBAYASHI
This paper proposes a closed-loop optimization framework to improve image coding efficiency by searching DCT coefficients at the equivalent subjective quality to original coding result. The proposed framework shares a basic idea currently adopted in speech coding that searches optimal codes in closed loop operation, evaluating the coded signal with perceptually weighted mean square error. To evaluate the perceptual quality in image coding, we introduce Masked PSNR that accounts masking effects, by which we apply the stepwise removal of subjectively negligible DCT coefficients. The result justifies the effectiveness of the proposed framework.

3:30, IMDSP-P1.6
DCT-DOMAIN BLIND MEASUREMENT OF BLOCKING ARTIFACTS IN DCT-CODED IMAGES
A. BOVIK, S. LIU
A method for DCT-domain blind measurement of blocking artifacts is proposed in this paper. By constituting a new block across any two adjacent blocks, the blocking artifact is modeled as a 2-D step function. A fast DCT-domain algorithm has been derived to constitute the new block and extract all parameters needed. Then an HVS based measurement of blocking artifacts is conducted. Experimental results have shown the effectiveness and stability of our method. The proposed technique can be used for online image/video quality monitoring and control in applications of DCT-domain image/video processing.

3:30, IMDSP-P1.7
CODING OF DIGITAL IMAGERY FOR TRANSMISSION OVER MULTIPLE NOISY CHANNELS
S. CHANNAPPAYYA, G. ABOUSLEMAN, L. KARAM
This paper presents a multiple description image coding scheme that facilitates the transmission of digital imagery over multiple noisy channels. The proposed scheme divides the image into smaller parts that are transmitted over the individual channels of an inverse multiplexing system. The division or splitting is done in such a fashion that it facilitates the interpolation of lost coefficients in the case of one or more channel failures. At the receiver, the image is reconstructed by proper assembly of the data received from each channel. In case of channel failure, the missing coefficients are estimated from the available data with the use of a novel post processing scheme. For operation over four noisy channels with various bit error probabilities, we investigate the quantitative and subjective performance with and without channel failures.

3:30, IMDSP-P1.8
ERROR RECOVERY IN JPEG2000 IMAGE TRANSMISSION
L. ATZORI, S. CORONA, D. GIUSTO
In this paper, the problem of bit-errors recovery in JPEG2000 images transmission is addressed, with particular attention to errors in the high-frequency components. In the HL and LH sub-bands, differently from the LL band, interpolation based recovering results to be often ineffective when more than few adjacent wavelet coefficients are missing. The solution proposed is then to apply a wavelet patch repetition procedure by predicting the similitude between the contour structure in the damaged area and its surroundings. To this aim, the correlation in the spatial structure, that is the contour information, existing between different sub-bands has been analyzed and exploited. Accordingly, the patch used to conceal the corrupted region is that obtained by minimizing a correlation measure with the spatial structure extracted from an adjacent not corrupted sub-band. Objective and subjective improvements have been obtained.

3:30, IMDSP-P1.9
STRUCTURE PRESERVING ERROR CONCEALMENT WITH DIRECTIONAL SMOOTHNESS MEASURE
Y. ZHU, S. SCHWARTZ, M. ORCHARD
We propose a directional smoothness measure for block-based error concealment through spatial correlation. Image structures revealed by consistent edge profiles are very important for subjective visual quality. We treat the problem of block reconstruction as consistent recovery of local image structures. The directional smoothness measure evaluates structural consistency along edge elongation and is used as the object function for block reconstruction. Corrupted DCT coefficients are recovered by smoothly extending various edge profiles from surrounding areas to missing blocks. The reconstruction is adaptive to local image structures. Consistent cross-edge sharpness and along-edge smoothness are maximally preserved during the reconstruction. The proposed concealment method demonstrates encouraging improvement both in the subjective image quality and in the reconstruction PSNR over conventional schemes. It is applicable to various spatial and spectral interleaving systems and a fast implementation is also proposed.

3:30, IMDSP-P1.10
NEW RELATIVE MULTIFRACTAL DIMENSION MEASURES
R. DANSEREAU, W. KINSNER
This paper introduces a new class of fractal dimension measures which we call relative multifractal measures. The relative multifractal measures developed are formed through a melding of the Renyi dimension spectrum, which is based on the Renyi generalized entropy, and relative entropy as given with the Kullback-Leibler distance. This new class of multifractal measures is then used to find the relative multifractal complexity differences between two signals, an image and its lossy approximation. It is proposed that relative multifractal measures can be used as the basis for a new form of signal and image quality measure based on signal complexity.

3:30, IMDSP-P1.11
INTELLIGENT COMPRESSION OF SAR IMAGERY USING MULTIRESOLUTION MARKOV MODELS
R. BONNEAU, G. ABOUSLEMAN
We present a system for coding synthetic aperture radar (SAR) imagery, whereby regions of interest and background information are coded independently of each other. A multiresolution constant-false-alarm-rate (CFAR) detection scheme is utilized to discriminate between target regions and natural clutter. Based upon the detected target regions, we apply less compression to targets, and more compression to background data. This methodology preserves relevant features of targets for further analysis, and preserves the background only to the extent of providing contextual information. The resulting system dramatically reduces the bandwidth/storage requirements of the digital SAR imagery, while preserving the target-specific utility of the imagery.