Development of a Method for Restoring Deteriorated Digital Images
Tae-Eun Kim
Tae-Eun Kim, Department of Multimedia, Namseoul University, South Korea, East Asian.
Manuscript received on 10 June 2019 | Revised Manuscript received on 17 June 2019 | Manuscript Published on 22 June 2019 | PP: 807-813 | Volume-8 Issue-8S2 June 2019 | Retrieval Number: H11350688S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: For image contents filmed by digital equipment, the object is recognized and photographed through the light reflected against it. If there is not any contamination in the reflected light, we can get image contents as we intended. However, if the light reflected against the object is contaminated, the degraded image contents are obtained. There is less contamination in the light reflected against objects in most interior spaces. On the other hand, most of image contents photographed during leisure sports activities or taken by a camera mounted on a drone are taken in an outdoor environment, and for such image contents photographed in an outdoor environment, the light reflected against the object is very likely to be contaminated. Therefore, this paper intends to solve the degradation problem of image contents through restoration of degraded image contents.Methods: This paper intends to solve the degradation problem of image contents through restoration of degraded image contents. In order to restore degraded images, an adaptive dark channel technique is proposed that generates edge map using standard deviation, and preserves edge with a weighting map using weight function. As adaptive dark channel preserves boundary and estimates the amount of light transmission, the naturally restored images can be obtained. As a result of conducting experiments involving aerial and underwater images, in can be confirmed that the degraded image contents are efficiently restored using the proposed method.Findings: This paper aims to figure out degree of degradation and to efficiently restore the degraded image contents degraded by particles in the atmosphere, and to this end, estimates atmospheric light and the amount of light transmission and restores images. In addition, this paper estimates distance from a single image.Applications: Image processing technique for restoring images proposed in this study can also be used for white balancing calculation, and the amount of light transmission can be used to estimate depth information of a single image. It is also possible to create high-quality image contents that can express a richer color after restoring the degraded image.
Keywords: Weight Function, Degraded Image, Adaptive Dark Channel Technique, Global Atmospheric Light , Edge Map Computer Visions.
Scope of the Article: Software Defined Networking and Network Function Virtualization