Abstract
Super resolution is a method that reconstructs a higher resolution image from single captured image or set of captured low resolution images. Super resolution imaging is used for several image processing applications like medical imaging, earth observation systems and surveillance systems. Image interpolation is one of the conventional methods used to enhance the resolution of the image. Basic linear interpolation methods like bilinear, bicubic give the blurred image as a result. Non-linear interpolation methods like New Edge Directed Interpolation (NEDI), Curvature based interpolation, neural network based interpolation enhance the image but has limitations like several artifacts. In this paper, a novel innovative approach is proposed in which using dual tree complex wavelet transform (DT-CWT), low and high frequency sub bands are generated. High frequency sub band images are interpolated using improved NEDI which is NEDI with a circular window and dynamic window. Improved NEDI (INEDI) algorithm proposed in the paper gives better results on high frequency components which lead to high resolution image without artifacts. Inverse DT-CWT is applied on interpolated sub bands to reconstruct high resolution image. Registration is applied on both images and shift adaptable bilinear interpolation is applied which reconstructs image into 4 interpolation factor. The proposed approach is verified for different interpolation factors and for different satellite images. The accuracy of proposed approach is verified by several contrast features. The algorithm proposed in this paper outperforms in comparison to state of the art algorithms.
Highlights
In various fields like medical imaging, remote sensing, recognition and computer graphics, high resolution image is desirable
Irani and Peleg[30] proposed super resolution reconstruction approach using iterative back-projection, where high resolution image is estimated by iteratively protruding error between feigned low resolution image via imaging blur and observed low resolution image
The effectiveness of proposed approach is proved by comparing it with different methods like bilinear, bicubic, New Edge Directed Interpolation (NEDI), DWT-RE[42], dual tree complex wavelet transform (DT-CWT)-RE[43], DT-CWTNLM-RE[44] for different satellite images in 7
Summary
In various fields like medical imaging, remote sensing, recognition and computer graphics, high resolution image is desirable. As pixel size of sensor reduces, the power of signal decreases This fact affects the quality of image. Image processing involves many images with lost detail due to a situation like improper adjustment of cameras, lighting defect or camera with low sensor cell. This type of lost detail of image can be retrieved using super resolution method. In different applications like medical imaging, remote sensing, object tracking[17] a small error can generate major problems. The paper is arranged as follows: Section 2 contains brief overview of different Super Resolution methods.
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