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Hybrid Domain Feature-Based Image Super-resolution Using Fusion of APVT and DWT

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1097))

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Abstract

Digital image-processing technique is used in image super-resolution for a variety of applications. In this paper, we propose hybrid domain feature-based image super-resolution using a fusion of Average Pixel Values Technique (APVT) and Discrete Wavelet Transform (DWT). The low-resolution (LR) images are considered and converted into high-resolution (HR) images using a novel technique of APTV by inserting an average of rows between rows and average of columns between columns to get HR images. The DWT is applied on HR images to obtain four bands. The HR images are downsampled, and to enhance image quality, histogram equalization (HE) is utilized. The LL band and HE matrix are added to obtain new LL band. The inverse DWT is applied on four bands to derive SR image. It is observed that the performance of the proposed method is better than existing methods.

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Kiran, P., Jabeen, F. (2020). Hybrid Domain Feature-Based Image Super-resolution Using Fusion of APVT and DWT. In: Hu, YC., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 1097. Springer, Singapore. https://doi.org/10.1007/978-981-15-1518-7_34

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