Showing papers on "Peak signal-to-noise ratio published in 1999"

Geometric-structure-based error concealment with novel applications in block-based low-bit-rate coding

Abstract: This paper first proposes a computationally efficient spatial directional interpolation scheme, which makes use of the local geometric information extracted from the surrounding blocks. The proposed error-concealment scheme produces results that are superior to those of other approaches, in terms of both peak signal-to-noise ratio and visual quality. Then a novel approach that incorporates this directional spatial interpolation at the receiver is proposed for block-based low-bit-rate coding. The key observation is that the directional spatial interpolation at the receiver can reconstruct faithfully a large percentage of the blocks that are intentionally not sent. A rate-distortion optimal way to drop the blocks is shown. The new approach can be made compatible with standard JPEG and MPEG decoders. The block-dropping approach also has an important application for dynamic rate shaping in transmitting precompressed videos over channels of dynamic bandwidth. Experimental results show that the proposed coding and rate-shaping systems can provide significant subjective and objective gains over conventional approaches.

Restoration of lossy compressed noisy images

Abstract: Noise degrades the performance of any image compression algorithm. However, at very low bit rates, image coders effectively filter noise that may he present in the image, thus, enabling the coder to operate closer to the noise free case. Unfortunately, at these low bit rates the quality of the compressed image is reduced and very distinctive coding artifacts occur. This paper proposes a combined restoration of the compressed image from both the artifacts introduced by the coder along with the additive noise. The proposed approach is applied to images corrupted by data-dependent Poisson noise and to images corrupted by film-grain noise when compressed using a block transform-coder such as JPEG. This approach has proved to be effective in terms of visual quality and peak signal-to-noise ratio (PSNR) when tested on simulated and real images.

Lapped orthogonal transform coding by amplitude and group partitioning

Abstract: Transform coding has been the focus of the research for image compression. In previous research, the Amplitude and Group Partitioning (AGP) coding scheme is proved to be a low complexity algorithm with higher performance, clearly one of the state-of-art transform coding techniques. However, the previous AGP is used along with the Discrete Cosine Transform (DCT) and the discrete wavelet transform. In this paper, a different transform, the Lapped Orthogonal Transform (LOT), replaces the DCT in conjunction with the AGP. This is the first time LOT and AGP have been combined in a coding method. The definition and design of the LOT are discussed. An objective metric to measure the performance of transform, coding gain, is calculated for both the DCT and the LOT. The LOT has slightly higher coding gain than the DCT. The principles of the LOT based AGP image codec (LOT-AGP) are presented and a complete codec, encoder and decoder, is implemented in software. The performance of the LOT-AGP is compared with other block transform coding schemes: the baseline JPEG codec and the DCT based AGP image codec (DCT- AGP) by both objective evaluation and subjective evaluation. The Peak Signal to Noise Ratio (PSNR) is calculated for these three coding schemes. The two AGP codecs are much better than the JPEG codec on PSNR, from about 1.7 dB to 3 dB depending on bit rate. The two AGP schemes have PSNR differences only to a small degree. Visually, the LOT-AGP has the best-reconstructed images among these three at all bit rates. In addition, the coding results of two other state-of-art progressive image codecs are cited for further comparison. One is the Set Partitioning in Hierarchical Trees (SPIHT) algorithm with a dyadic wavelet transform, and the other is Tran and Nguyen's method with the generalized LOT transform. The AGP coding and the adaptive Huffman entropy coding of LOT-AGP are less complex and the memory usage is smaller than in these two progressive codecs. Comparing these three codecs, i.e. the LOT-AGP and the two progressive codecs in PSNR small only small differences in PSNR. SPIHT has about 1 dB higher PSNR than the LOT-AGP and Tran and Nguyen's method for the test image Lena. For the test image Barbara, the PSNR of the LOT- AGP is about 0.5 dB higher than that of the SPIHT and 0.5 dB lower than that of Tran and Nguyen's method. This low- complexity and high performance codec may provide a new direction for the implementation of image compression.

Performance of lossy compression algorithms from statistical and perceptual metrics

Abstract: The performance of compression algorithms is traditionally evaluated by statistical metrics such as mean square error (MSE) and peak signal-to-noise ratio (PSNR). However it is well known that these metrics do not always correlate with visual perception. We have implemented a well known perceptual metric and evaluated the performance of a number of recently developed high fidelity compression algorithms using perceptual as well as statistical metrics. Our preliminary results do not indicate a consistent correlation between the perceptual metric used and subjective ranking.

Wavelet Image Coding Using Trellis

Abstract: Recent progresses in wavelet image coding have brought the field into its maturity. Major developments in the process are rate-distortion (R-D) based wavelet packet transfor- mation, zerotree quantization, subband classification and trellis- coded quantization, and sophisticated context modeling in en- tropy coding. Drawing from past experience and recent in- sights, we propose a new wavelet image coding technique with trellis coded space-frequency quantization (TCSFQ). TCSFQ aims to explore space-frequency characterizations of wavelet image representations via R-D optimized zerotree pruning, trellis- coded quantization, and context modeling in entropy coding. Experiments indicate that the TCSFQ coder achieves twice as much compression as the baseline JPEG coder does at the same peak signal to noise ratio (PSNR), making it better than all other coders described in the literature (1).

Optimization design of filter banks in subband image coding

Abstract: In this paper we present a new optimization-based method for designing filter banks in subband image coding. We formulate the design problem as a nonlinear optimization problem whose objective consists of both the performance metrics of the image coder; such as the peak signal to noise ratio (PSNR), and those of individual filters. In contrast to previous methods that design filter banks separately from the other operations in image coding, our formulation allows us to search for the filters in the context of an image coder to maximize coding quality. Due to the nonlinear nature of the performance metrics, the optimization problem is solved by using simulating annealing. In our method, we first apply the optimization method to find good filter banks for individual training image and then select the one that performs best across all training images to be the final solution. In experimental results, toe show that the filter bank designed by our method improves the coding quality of the best existing filter bank in terms of PSNR on nine benchmark images.

3D wavelet-based codec for lossy compression of pre-scan-converted ultrasound video

Abstract: We present a wavelet-based video codec based on a 3-D (x,y,t) wavelet transformer, a uniform quantizer/dequantizer and anarithmetic encoder/decoder. The wavelet transformer uses biorthogonal (9,7) Antonini wavelets in the two spatial dimensionsand Haar wavelets in the time dimension. Multiple levels of decomposition are supported. The codec has been applied to pre-scan-converted (r-theta or poiar coordinate) ultrasound image data and does not produce the type of blocking artifacts thatoccur in MPEG-compressed video. The PSNR (peak signal to noise ratio) at a given compression rate increases with thenumber of levels of decomposition: for our data at 50: 1 compression, the PSNR increases from 1 8.4 dB at one level to 24.0dB at four levels of decomposition. Our 3-D wavelet-based video codec provides the high compression rates required totransmit diagnostic ultrasound video over existing low bandwidth links without introducing the blocking artifacts which havebeen demonstrated to diminish clinical utility.Keywords: Wavelets, video compression, video codec, diagnostic ultrasound

Filter evaluation in image deblocking by wavelet thresholding

Abstract: Blockiness occurs when using compression techniques based a block discrete cosine transform (BDCT) at high compression ratios An approach for reducing the blockiness is based on wavelet thresholding We evaluate various types of wavelet filters for use in this deblocking technique The evaluation criteria used include the peak signal-to-noise ratio (PSNR), edge variance (EV) and visual performance The results show that, among the wavelets studied, the Coiflet-5 filters give best performance for the deblocking purpose

Simulation of Graded Video Impairment by Weighted Summation: Validation of the Methodology | NIST

Abstract: The investigation examines two methodologies by which to control the impairment level of digital video test materials. Such continuous fine-tuning of video impairments is required for psychophysical measurements of human visual sensitivity to picture impairments induced by MPEG-2 compression. Because the visual sensitivity data will be used to calibrate objective and subjective video quality models and scales, the stimuli must contain realistic representations of actual encoder-induced video impairments. That is, both the visual and objective spatio-temporal response to the stimuli must be similar to the response to impairments induced directly by an encoder. The first method builds a regression model of the Peak Signal To Noise Ratio (PSNR) of the output sequence as a function of the bit rate specification used to encode a given video clip. The experiments find that for any source sequence, a polynomial function can be defined by which to predict the encoder bit rate that will yield a sequence having any targeted PSNR level. In a second method, MPEG-2-processed sequences are linearly combined with their unprocessed video sources. Linear regression is used to relate PSNR to the weighting factors used in combining the source and processed sequences. Then the "synthetically" adjusted impairments are compared to those created via an encoder. Visual comparison is made between corresponding I-, B-, and P-frames of the synthetically generated sequences and those processed by the codec. Also, PSNR comparisons are made between various combinations of source sequence, the MPEG-2 sequence used for mixing, the mixed sequence, and the codec-processed sequence. Both methods are found to support precision adjustment of impairment level adequate for visual threshold measurement. The authors caution that some realism may be lost when using the weighted summation method with highly compression-impaired video.