Jiangling Guo

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Backward Coding of Wavelet Trees (BCWT) is an extremely fast wavelet-tree-based image coding algorithm. Utilizing a unique backward coding algorithm, BCWT also provides a rich set of features such as resolution-scalability, extremely low memory usage, and extremely low complexity. However, BCWT in its original form inherits one drawback also existing in(More)
OBJECTIVE Visual assessment of digitized cervigrams through the Internet needs to be optimized. The National Cancer Institute and National Library of Medicine are involved in a large effort to improve colposcopic assessment and, in preparation, are conducting methodologic research. MATERIALS AND METHODS We selected 50 cervigrams with diagnoses ranging(More)
A new approach of backward coding of wavelet trees (BCWT) is presented. Contrary to the common "forward" coding of wavelet trees from the highest level (lowest resolution), the new approach starts coding from the lowest level and goes backward by building a map of maximum quantization levels of descendants. BCWT eliminates several major bottlenecks of(More)
Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic(More)
Wavelet tree-based image compression algorithms have excellent rate distortion performance. However, they have a major drawback in their memory consumption. A new approach based on backward coding of wavelet trees (BCWT) has been recently developed. Although the BCWT algorithm itself uses much less memory than the SPIHT algorithm, the total system memory(More)
Studies have shown that eyeglasses have negative impact on the face recognition. Based on the investigation of face features changes introduced by eyeglasses, and the fact that phase congruency is not sensitive to the intensity and contrast, we proposed an eyeglasses detection and removal algorithm based on phase congruency and progressive inpainting.(More)
ii ACKNOWLEDGEMENTS If I have seen this far, it is because I have stood on the shoulders of giants.-Sir Isaac Newton I am highly indebted to my advisor, Dr. Sunanda Mitra for providing consistent support and guidance both technically and financially during my Master's program. Her timely suggestions and valuable advice enabled the successful completion of(More)