The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-91-2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-91-2020
12 Aug 2020
 | 12 Aug 2020

IMAGE BLUR DETECTION METHOD BASED ON GRADIENT INFORMATION IN DIRECTIONAL STATISTICS

Y. Takahashi, C. Kuhara, and H. Chikatsu

Keywords: Aerial Photogrammetry, Motion Blur, Image Inspection, Directional Statistics, Local Features

Abstract. Images are visually inspected for defects that affect downstream operations and qualitatively evaluated immediately after they are acquired. Therefore, there is concern that an increase in the number of images taken affects the quality and process of inspections. Among the defects qualitatively detected in visual inspections, blurring is a serious one, despite its low rate of appearance. However, the blurry images detected in the visual inspections can only be solved by the take another photograph. For this reason, it is not acceptable for any blurry images to be missed in the visual inspections. Therefore, quantitative evaluations are an issue when inspecting photographed images. In the present study, its characteristics in aerial photography were investigated and it was established that motion blur occurs in aerial photography. The motion blur is a condition in which the subject appears to have drifted. We focused on the gradient direction of the image, which is considered to be concentrated in a certain direction. The concept of directional statistics was used to statistically process the gradient direction. The evaluation values calculated from the gradient direction statistics tended to increase with the amount of blurring in the aerial photographs. An experiment was conducted to investigate whether images with blurring could be detected in a large number of aerial photographs. As a result, we were able to successfully detect blurred images that had been overlooked during the visual inspection as well as the images that had been previously detected during the visual inspection.