Comparison of different algorithms to improve the quality of image (Record no. 20204)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | a |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20231130103439.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 231130b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 22236 |
| Author | Sonavane, Mayur M. |
| 245 ## - TITLE STATEMENT | |
| Title | Comparison of different algorithms to improve the quality of image |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.13(4), Jul-Aug |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Haryana |
| Name of publisher, distributor, etc. | IOSR - International Organization of Scientific Research |
| Year | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 7-13p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Super-resolution (SR) become the most important task in image processing because of requirement of high quality of images. It becomes popular in technology like computer vision and pattern recognition. In Single Image Super-resolution (SR) uses the sequences of single low resolution (LR) images from high resolution (HR) to improve the quality of image. The SR is an image processing problem which aims to generate a high resolution (HR) image from low resolution input image. The SR is difficult because of the missing information in the given LR image. Thus in SR it is very important to boost the reconstruction performance so that, there is need of effective prior knowledge. The prior knowledge of image will solve the problem to improve the quality of generated image. The main aim of SR is to generate the HR image with good visual perception as similar as original image. The paper compare two methods of SR that is bi-linear method, and direction group sparsity of image method that is proposed one. These methods will evaluate the accuracy, subjective visual effect, quality of image, time complexity and PSNR, etc. These calculations will enhance nature of picture like better visual impact quality, lower reconstruction error and adequate calculation proficiency, and so on. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4619 |
| Topical term or geographic name entry element | EXTC Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 7286 |
| Co-Author | Agrawal, S. S. |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Gurgaon International Organization Of Scientific Research (IOSR) |
| Title | IOSR journal of VLSI and signal processing (IOSR-JVSP) |
| International Standard Serial Number | 2319 – 4197 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://www.iosrjournals.org/iosr-jvlsi/papers/vol13-issue4/B13040713.pdf |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 2023-11-30 | 2023-1622 | 2023-11-30 | 2023-11-30 | Articles Abstract Database |