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In the remote sensing community, accurate image registration is the prerequisite of the subsequent application of remote sensing images. Phase correlation based image registration has drawn extensive attention due to its high accuracy and high efficiency. However, when the Discrete Fourier Transform (DFT) of an image is computed, the image is implicitly assumed to be periodic. In practical application, it is impossible to meet the periodic condition that opposite borders of an image are alike, and image always shows strong discontinuities across the frame border. The discontinuities cause a severe artifact in the Fourier Transform, namely the known cross structure composed of high energy coefficients along the axes. Here, this phenomenon was referred to as effect of image border. Even worse, the effect of image border corrupted its registration accuracy and success rate. Currently, the main solution is blurring out the border of the image by weighting window function on the reference and sensed image. However, the approach also inevitably filters out non-border information of an image. The existing understanding is that the design of window function should filter as little information as possible, which can improve the registration success rate and accuracy of methods based on phase correlation. In this paper, another approach of eliminating the effect of image border is proposed, namely decomposing the image into two images: one being the periodic image and the other the smooth image. Replacing the original image by the periodic one does not suffer from the effect on the image border when applying Fourier Transform. The smooth image is analogous to an error image, which has little information except at the border. Extensive experiments were carried out and showed that the novel algorithm of eliminating the image border can improve the success rate and accuracy of phase correlation based image registration in some certain cases. Additionally, we obtained a new understanding of the role of window function in eliminating the effect of image border, which is helpful for researchers to select the optimal method of eliminating the effect of image border to improve the registration success rate and accuracy.
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CONTEXT: Epigenetic alterations in suppressor of cytokine signalling 3 (SOCS3) have been suggested as a potential biomarker in glioma. OBJECTIVE: To investigate whether SOCS3 methylation could act as a biomarker for glioma grading and prognosis. MATERIALS AND METHODS: Glioma samples were evaluated by pyrosequencing and quantitative reverse transcription-polymerase chain reaction (qRT-PCR). RESULTS: SOCS3 promoter methylation was more frequent in the WHO III and (anaplastic) oligoastrocytomas group. SOCS3 methylation status was significantly inversely correlated with mRNA expression level. Mutant IDH1 caused marked increase in SOCS3 methylation. CONCLUSION: SOCS3 methylation is a potential biomarker for grading and prognosis in human glioma.
RESUMO
Spectral difference is an important aspect for extracting shadows of buildings. Based on the analysis of the relationship between the building heights and the shadows in ALOS Images, the paper presents the principle and the method for building heights estimation in a city from the shadows of an image, and works out a feasible approach to determining shadow zones in a panchromatic ALOS Images. It has also contributed a standard process for extracting buildings distribution information of different heights in a city from the shadows in a panchromatic ALOS Images. A result with about 87.6% accuracy has been achieved while applying this technique to Tianjin City, which has demonstrated prospective applications of satellite remote sensing to urban purposes.