Detail enhancement and segmentation extraction of cladding image based on super resolution

2021 ◽  
Author(s):  
Mengyu Tang ◽  
Zhenying Xu ◽  
Ziqian Wu ◽  
Qiling Li ◽  
Jun Ling ◽  
...  
Keyword(s):  
Super Resolution ◽  
Detail Enhancement

scholarly journals Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

Sensors ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 498 ◽  
Author(s):  
Hong Zhu ◽  
Xinming Tang ◽  
Junfeng Xie ◽  
Weidong Song ◽  
Fan Mo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Super Resolution ◽  
Remote Sensing Images ◽  
Multi Scale ◽  
Spatio Temporal ◽  
Detail Enhancement

scholarly journals SUPER RESOLUTION RECONSTRUCTION BASED ON ADAPTIVE DETAIL ENHANCEMENT FOR ZY-3 SATELLITE IMAGES

2016 ◽  
Vol III-7 ◽  
pp. 213-217 ◽  
Author(s):  
Hong Zhu ◽  
Weidong Song ◽  
Hai Tan ◽  
Jingxue Wang ◽  
Di Jia
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Satellite Images ◽  
Interpolation Method ◽  
Super Resolution ◽  
Bilateral Filter ◽  
Redundant Information ◽  
Evaluation Standard ◽  
Detail Enhancement ◽  
Image Details

Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

scholarly journals Restoration and Enhancement of Historical Stereo Photos

2021 ◽  
Vol 7 (7) ◽  
pp. 103
Author(s):  
Marco Fanfani ◽  
Carlo Colombo ◽  
Fabio Bellavia
Keyword(s):  
Super Resolution ◽  
Input Image ◽  
Visual Media ◽  
Consistency Checking ◽  
Single Image ◽  
Original Algorithm ◽  
Digital Restoration ◽  
Fully Automatic ◽  
Comparative Results ◽  
Detail Enhancement

Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed, referred to as Stacked Median Restoration plus (SMR+). The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically and photometrically. Restoration is then accomplished in three steps: (1) image fusion according to the stacked median operator, (2) low-resolution detail enhancement by guided supersampling, and (3) iterative visual consistency checking and refinement. Each step implements an original algorithm specifically designed for this work. The restored image is fully consistent with the original content, thus improving over the methods based on image hallucination. Comparative results on three different datasets of historical stereograms show the effectiveness of the proposed approach, and its superiority over single-image denoising and super-resolution methods. Results also show that the performance of the state-of-the-art single-image deep restoration network Bringing Old Photo Back to Life (BOPBtL) can be strongly improved when the input image is pre-processed by SMR+.

scholarly journals Deep Networks With Detail Enhancement for Infrared Image Super-Resolution

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 158690-158701
Author(s):  
Yifan Yang ◽  
Qi Li ◽  
Chenwei Yang ◽  
Yannian Fu ◽  
Huajun Feng ◽  
...  
Keyword(s):  
Infrared Image ◽  
Super Resolution ◽  
Deep Networks ◽  
Image Super Resolution ◽  
Detail Enhancement

scholarly journals SUPER RESOLUTION RECONSTRUCTION BASED ON ADAPTIVE DETAIL ENHANCEMENT FOR ZY-3 SATELLITE IMAGES

2016 ◽  
Vol III-7 ◽  
pp. 213-217 ◽  
Author(s):  
Hong Zhu ◽  
Weidong Song ◽  
Hai Tan ◽  
Jingxue Wang ◽  
Di Jia
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Satellite Images ◽  
Interpolation Method ◽  
Super Resolution ◽  
Bilateral Filter ◽  
Redundant Information ◽  
Evaluation Standard ◽  
Detail Enhancement ◽  
Image Details

Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

Detail enhancement of image super-resolution based on detail synthesis

2017 ◽  
Vol 50 ◽  
pp. 21-33 ◽  
Author(s):  
Jinsheng Xiao ◽  
Enyu Liu ◽  
Ling Zhao ◽  
Yuan-Fang Wang ◽  
Wenbin Jiang
Keyword(s):  
Super Resolution ◽  
Image Super Resolution ◽  
Detail Enhancement

Super-Resolution Microscopy in Studying the Structure and Function of the Cell Nucleus

Acta Naturae ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 42-51
Author(s):  
S. S. Ryabichko ◽  
◽  
A. N. Ibragimov ◽  
L. A. Lebedeva ◽  
E. N. Kozlov ◽  
...  
Keyword(s):  
Cell Nucleus ◽  
Super Resolution ◽  
Structure And Function ◽  
And Function ◽  
Super Resolution Microscopy
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