Image Restoration Quality Measurement using Noise Filters

The aim of this project is to implement different features of image restoration. We consider a vectorised picture and take pictures of it with our mobile for two configurations, the first lit by natural light, the second without the light. Those photos apply different transformations on the original...

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Bibliographic Details
Main Authors: Amitabh, K. (Author), Debnath, T. (Author), Paul, S. (Author)
Format: Article
Language:English
Published: Seventh Sense Research Group 2023
Subjects:
Online Access:View Fulltext in Publisher
View in Scopus
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001 10.14445-23488549-IJECE-V10I2P101
008 230529s2023 CNT 000 0 und d
020 |a 23488549 (ISSN) 
245 1 0 |a Image Restoration Quality Measurement using Noise Filters 
260 0 |b Seventh Sense Research Group  |c 2023 
300 |a 5 
856 |z View Fulltext in Publisher  |u https://doi.org/10.14445/23488549/IJECE-V10I2P101 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159330407&doi=10.14445%2f23488549%2fIJECE-V10I2P101&partnerID=40&md5=1f763d8d3003a97d4d6c945d5c58def9 
520 3 |a The aim of this project is to implement different features of image restoration. We consider a vectorised picture and take pictures of it with our mobile for two configurations, the first lit by natural light, the second without the light. Those photos apply different transformations on the original image as rotation, change of the scale, integration of unwanted environment in the picture, etc. We will see a method to restore those photos and compare them to the original image. The comparison will be made by using two indicators: the Peak Signal Noise Ratio (PSNR), measuring the quality of reconstruction of the image, and the Structural Similarity Index (SSIM), evaluating the similarity between pixels. Finally, the complementary analysis will be performed to increase the restoration quality between the pictures, like using a noise reduction filter or function to increase the correspondence between histograms. © 2023 Seventh Sense Research Group®. 
650 0 4 |a Histogram equalization 
650 0 4 |a Noise reduction 
650 0 4 |a Peak signal to Noise ratio 
650 0 4 |a Sharpening 
650 0 4 |a Structural Similarity Index 
700 1 0 |a Amitabh, K.  |e author 
700 1 0 |a Debnath, T.  |e author 
700 1 0 |a Paul, S.  |e author 
773 |t SSRG International Journal of Electronics and Communication Engineering