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Super-Resolution Technique using Sparse Representation with an Overcomplete Dictionary

หน่วยงาน จุฬาลงกรณ์มหาวิทยาลัย

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ชื่อเรื่อง : Super-Resolution Technique using Sparse Representation with an Overcomplete Dictionary
นักวิจัย : Seno Purnomo
คำค้น : Closed-circuit television , Video surveillance , Electronic surveillance , Television cameras -- Image quality , Image processing -- Digital techniques , High resolution imaging , Image reconstruction , Imaging systems -- Image quality
หน่วยงาน : จุฬาลงกรณ์มหาวิทยาลัย
ผู้ร่วมงาน : Supavadee Aramvith , Suree Pumrin , Chulalongkorn University. Faculty of Engineering
ปีพิมพ์ : 2554
อ้างอิง : http://cuir.car.chula.ac.th/handle/123456789/30731
ที่มา : -
ความเชี่ยวชาญ : -
ความสัมพันธ์ : -
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Thesis (M.Eng.)--Chulalongkorn University, 2011

Image super resolution is very important and is also considered as a challenging problem in image applications. The main researches are about how to bring back missing information in generating higher resolution image given that there is only information from a single low resolution image. Conventional methods such as interpolation could be applied to estimate the missing pixel information. However, there is still not enough information to generate the high resolution image. Thus, the resulting image may look blurred and lacks high resolution detail. In this thesis, sparse representation is used as a fundamental method to solve the problem. In training step, we propose an efficient clustering dictionary to design an overcomplete dictionary. Firstly, we prepare training set as an initial dictionary. We then perform efficient sparse coding to generate basis matrix. The error of the dictionary is reduced using singular value decomposition. In solution step, we propose Elastic Net as a solution of sparse representation problem. Experiments demonstrated that our proposed method can generate high resolution images with better visual quality when compared with conventional method such as Bicubic interpolation. Our method can give smaller Root Mean Square Error (RMSE) value than other known interpolation methods. Smaller RMSE implies the higher accuracy in the recognition of face, license plate, and other objects. Experiments also proved that our proposed method is applicable in video super-resolution. We use combination of sparse-representation method and analytical method to reduce number of skipped frames while retained the acceptable quality of generated high resolution video.

บรรณานุกรม :
Seno Purnomo . (2554). Super-Resolution Technique using Sparse Representation with an Overcomplete Dictionary.
    กรุงเทพมหานคร : จุฬาลงกรณ์มหาวิทยาลัย.
Seno Purnomo . 2554. "Super-Resolution Technique using Sparse Representation with an Overcomplete Dictionary".
    กรุงเทพมหานคร : จุฬาลงกรณ์มหาวิทยาลัย.
Seno Purnomo . "Super-Resolution Technique using Sparse Representation with an Overcomplete Dictionary."
    กรุงเทพมหานคร : จุฬาลงกรณ์มหาวิทยาลัย, 2554. Print.
Seno Purnomo . Super-Resolution Technique using Sparse Representation with an Overcomplete Dictionary. กรุงเทพมหานคร : จุฬาลงกรณ์มหาวิทยาลัย; 2554.