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標題: 使用影像修補技術消除數位單眼相機感光元件染塵
作者: 吳俊霖 
關鍵字: Sensor dust;感光元件染塵;Image inpainting;Texture synthesis;Noise removal;影像修補;材質合成;雜訊去除
出版社: 國立中興大學工學院;Airiti Press Inc.
Project: 興大工程學刊, Volume 18, Issue 3, Page(s) 187-198.

The digital cameras are becoming more and more popular nowadays. Digital SLRs not only allow photographers to use inter-changeable lenses to get different ranges of zoom and depth of field, but also give the users more control, it helps to take a better picture. Recently the number of digital SLR users is rising steadily as the equipments drop in price. However, unlike film cameras, current digital SLRs suffer from a frustrating weakness: sensor dust. It is obvious that the dust can damage the photos seriously. Clearning dust on sensors is almost universally warned against by camera makers. If we remove the dust directly by the sensor brush, we might scratch or otherwise damage the cover glass over the sensor, therefore are responsible for the cost of repairs. Camera manufacturers have introduced the dust-reduction solution that involves anti-static coatings and vibration-cleaning of the low-pass filter. However, they can not remove the dust particles with high viscosity effectively.
Some photographers propose to correct this problem in software. The traditional noise reduction methods such as median filter do not perform well in removing the dust spots, since the size of the noise in digital photos caused by dust is large. Some image editing software such as Adobe Photoshop and Ulead Photoimpact also provide the healing brush and clone stamp to stamp out the dust specs, one at a time. However, it is a time-consuming and tedious process if we are taking many photos that suffer from this problem. In this paper, we deveop an automatic spots removal algorithm based on the inpainting technique. We first propose a noise detection algorithm to identify the dust spots, it uses Sobel filter and the process is fully automatic. A fast exemplar-based image inpainting approach is then proposed to fill holes of dust spots in images, it achieves accurate propagation of linear structures. Several examples on real images are given to demonstrate the effectiveness of the proposed method.
ISSN: 1017-4397
Appears in Collections:第18卷 第3期

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