Abstract
Due to the inherent low-contrast in Electronic Portal Images (EPI), the perception quality of EPI has certain gap to the expectation of most physicians. It is essential to have effective post-processing methods to enhance the visual quality of EPI. However, only limited efforts had been paid to this issue in the past decade. To this problem, an integrated approach featuring automatic thresholding is developed and presented in this article. Firstly, Gray-Level Grouping (GLG) is applied to improve the global contrast of the whole image. Secondly, Adaptive Image Contrast Enhancement (AICE) is used to refine the local contrast within a neighborhood. Finally, a simple spatial filter is employed to reduce noises. The experimental results indicate that the proposed method greatly improves the visual perceptibility as compared with previous approaches.
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Hung, MH., Chu, SC., Roddick, J.F., Pan, JS., Shieh, CS. (2010). An Effective Image Enhancement Method for Electronic Portal Images. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16696-9_19
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DOI: https://doi.org/10.1007/978-3-642-16696-9_19
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