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Showing papers by "William A. Pearlman published in 1988"


Journal ArticleDOI
TL;DR: An adaptation procedure is introduced for determining in real-time the extent on the analysis window in point estimation of signals corrupted by additive noise and the visual results of the signal and image restorations exhibit superior preservation of edge and detail and suppression of noise for the filters with adaptive windows.
Abstract: An adaptation procedure is introduced for determining in real-time the extent on the analysis window in point estimation of signals corrupted by additive noise. In the tasks of restoring a noisy one-dimensional test signal and a two-dimensional noisy image, mean, median and minimum-mean-square-error filters are compared with fixed and adaptive window implementations. The visual results of the signal and image restorations exhibit superior preservation of edge and detail and suppression of noise for the filters with adaptive windows. >

52 citations


Proceedings ArticleDOI
11 Apr 1988
TL;DR: Simulations with natural and multimodality medical images provide reconstructions with nearly uniform block distortion and very high visual and measurable quality at low rates.
Abstract: A block discrete-cosine transform coding scheme is implemented with a different rate assignment to each block for the purpose of maintaining a constant distortion per block. A spectral estimate is calculated for every block. Overhead rate and computation for adaptation are kept to a reasonable level through characterization of the block's estimated spectrum by a one-dimensional autoregressive model. Simulations with natural and multimodality medical images provide reconstructions with nearly uniform block distortion and very high visual and measurable quality at low rates. >

9 citations


Proceedings ArticleDOI
11 Apr 1988
TL;DR: It is proved that optimal coding of image subbands achieves the ultimate rate-distortion performance for Gaussian sources with squared-error distortion.
Abstract: It is proved that optimal coding of image subbands achieves the ultimate rate-distortion performance for Gaussian sources with squared-error distortion. Optimal performance is achieved only asymptotically with infinite-size source sequences. The approach of the rate-distortion function of finite-size sequences to its limit is investigated and a bound is derived that shows a potentially closer approach for coding subbands that for the full band. A suboptimal realization of an optimal tree coding method is used to encode both the full-band image and its subbands at 1.0 bit per pixel. The subband tree-coded image is more than 2 dB better in SNR and its overall performance is nearly comparable to that of the best schemes known to date. >

4 citations


Proceedings ArticleDOI
18 Jan 1988
TL;DR: A new estimation criterion, called the minimum-error, minimum-correlation (MEMC) criterion, is applied to the point estimation of images in additive noise in conjunction with calculation of local statistical parameters in an adaptive analysis window.
Abstract: A new estimation criterion, called the minimum-error, minimum-correlation (MEMC) criterion, is applied to the point estimation of images in additive noise in conjunction with calculation of local statistical parameters in an adaptive analysis window. The MEMC estimator produces sharper and hence more visually pleasing restorations than the usual minimum mean squared error estimator and the use of adaptive analysis windows tends to isolate the locally stationary portions of the image in calculation of image statistics. As most of the remaining noise in these restorations resides on the edges within the images, a postprocessing step of edge detection and edge smoothing is then applied for its reduction. Such image restorations are compared to those of minimum mean squared error in both fixed and adaptive window implementations.

1 citations


Proceedings ArticleDOI
25 Oct 1988
TL;DR: A tree code, asymptotically optimal for stationary Gaussian sources and squared error distortion, is used to encode transforms of image sub-blocks and the results at the higher search intensities outperform a parallel simulation with quantization replacing tree coding.
Abstract: A tree code, asymptotically optimal for stationary Gaussian sources and squared error distortion [2], is used to encode transforms of image sub-blocks. The variance spectrum of each sub-block is estimated and specified uniquely by a set of one-dimensional auto-regressive parameters. The expected distortion is set to a constant for each block and the rate is allowed to vary to meet the given level of distortion. Since the spectrum and rate are different for every block, the code tree differs for every block. Coding simulations for target block distortion of 15 and average block rate of 0.99 bits per pel (bpp) show that very good results can be obtained at high search intensities at the expense of high computational complexity. The results at the higher search intensities outperform a parallel simulation with quantization replacing tree coding. Comparative coding simulations also show that the reproduced image with variable block rate and average rate of 0.99 bpp has 2.5 dB less distortion than a similarly reproduced image with a constant block rate equal to 1.0 bpp.