IMAGE Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition
Summary (1 min read)
Introduction
- One of the commonly used techniques for image resolution enhancement is Interpolation.
- The proposed technique uses DWT to decompose a low resolution image into different subbands.
II. PROPOSED IMAGE RESOLUTION ENHANCEMENT
- In image resolution enhancement by using interpolation the main loss is on its high frequency components (i.e., edges), which is due to the smoothing caused by interpolation.
- In order to increase the quality of the super resolved image, preserving the edges is essential.
- The redundancy and shift invariance of the DWT mean that DWT coefficients are inherently interpolable [9].
- One level DWT (with Daubechies 9/7 as wavelet function) is used to decompose an input image into different subband images.
- Therefore, instead of using low frequency subband, which contains less information than the original high resolution image, the authors are using the input image for the interpolation of low frequency subband image.
III. RESULTS AND DISCUSSIONS
- Note that the input low resolution images have been obtained by down-sampling the original high resolution images.
- Table I compares the PSNR performance of the proposed technique using bicubic interpolation with conventional and state-of-art resolution enhancement techniques: bilinear, bicubic, WZP, NEDI, HMM, HMM SR, WZP-CS, WZP-CS-ER, DWT SR, CWT SR, and regularity-preserving image interpolation.
- Additionally, in order to have more comprehensive comparison, the performance of the super resolved image by using SWT only (SWT-SR) is also included in the table.
- The results in Table I indicate that the proposed technique over-performs the aforementioned conventional and state-of-art image resolution enhancement techniques.
IV. CONCLUSION
- This work proposed an image resolution enhancement technique based on the interpolation of the high frequency subbands obtained by DWT, correcting the high frequency subband estimation by using SWT high frequency subbands, and the input image.
- The interpolated high frequency subband coefficients have been corrected by using the high frequency subbands achieved by SWT of the input image.
- An original image is interpolated with half of the interpolation factor used for interpolation the high frequency subbands.
- Afterwards all these images have been combined using IDWT to generate a super resolved imaged.
- The proposed technique has been tested on well-known benchmark images, where their PSNR and visual results show the superiority of proposed technique over the conventional and state-of-art image resolution enhancement techniques.
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Citations
602 citations
Cites background from "IMAGE Resolution Enhancement by Usi..."
...This allows exploiting the self-similarities between local neighboring regions [356], [516]....
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...For example, in [516] the input image is first decomposed into subbands....
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...Frequency (Wavelet) [79], [143], [150], [162], [179], [237], [257], [302], [320], [345], [356], [390], [399], [423], [425], [436], [441], [447], [459], [476], [487], [489], [509], [516], [549], [564], [565], [565], [600]...
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133 citations
Cites methods from "IMAGE Resolution Enhancement by Usi..."
...Demirel and Anbarjafari [56] demonstrated the inverse discrete wavelet decomposition (IDWT) method, which decomposed an image by DWT to get several subbands images, and then interpolated the high-frequency sub-band and the raw image; the coefficients obtained by interpolating the high-frequency subband image were amended by a stationary wavelet transform....
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...Demirel and Anbarjafari [56] demonstrated the inverse discrete wavelet decomposition (IDWT) method, which decomposed an image by DWT to get several subbands images, and then interpolated the high-frequency sub-band and the raw image; the coefficients obtained by interpolating the high-frequency sub-...
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127 citations
103 citations
99 citations
Cites methods from "IMAGE Resolution Enhancement by Usi..."
...…proposed SR procedure with other similar techniques, such as the following: Demirel - Anbarjafari Super Resolution [8], Wavelet Domain Image Resolution Enhancement Using Cycle-Spinning [9], Image Resolution Enhancement by using Discrete and Stationary Wavelet Decomposition 1545-598X © 2014 IEEE....
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References
17,693 citations
"IMAGE Resolution Enhancement by Usi..." refers background in this paper
...Image resolution enhancement in the wavelet domain is a relatively new research topic and recently many new algorithms have been proposed [4]–[7]....
[...]
1,933 citations
"IMAGE Resolution Enhancement by Usi..." refers methods in this paper
...Table I compares the PSNR performance of the proposed technique using bicubic interpolation with conventional and state-of-art resolution enhancement techniques: bilinear, bicubic, WZP, NEDI, HMM, HMM SR, WZP-CS, WZP-CS-ER, DWT SR, CWT SR, and regularity-preserving image interpolation....
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...Digital Object Identifier 10.1109/TIP.2010.2087767 — regularity-preserving image interpolation [7]; — new edge-directed interpolation (NEDI) [10]; — hidden Markov model (HMM) [11]; — HMM-based image super resolution (HMM SR) [12]; — WZP and cycle-spinning (WZP-CS) [13]; — WZP, CS, and edge rectification (WZP-CS-ER) [14]; — DWT based super resolution (DWT SR) [15]; — complex wavelet transform based super resolution (CWT SR) [5]....
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...The state-of-art techniques used for comparison purposes are the following: — regularity-preserving image interpolation [7]; — new edge-directed interpolation (NEDI) [10]; — hidden Markov model (HMM) [11]; — HMM-based image super resolution (HMM SR) [12]; — WZP and cycle-spinning (WZP-CS) [13]; — WZP, CS, and edge rectification (WZP-CS-ER) [14]; — DWT based super resolution (DWT SR) [15]; — complex wavelet transform based super resolution (CWT SR) [5]....
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1,783 citations
334 citations
"IMAGE Resolution Enhancement by Usi..." refers background or methods in this paper
...The state-of-art techniques used for comparison purposes are the following: — regularity-preserving image interpolation [7]; — new edge-directed interpolation (NEDI) [10]; — hidden Markov model (HMM) [11]; — HMM-based image super resolution (HMM SR) [12]; — WZP and cycle-spinning (WZP-CS) [13]; — WZP, CS, and edge rectification (WZP-CS-ER) [14]; — DWT based super resolution (DWT SR) [15]; — complex wavelet transform based super resolution (CWT SR) [5]....
[...]
...Image resolution enhancement in the wavelet domain is a relatively new research topic and recently many new algorithms have been proposed [4]–[7]....
[...]
331 citations
"IMAGE Resolution Enhancement by Usi..." refers background or methods in this paper
...The interpolated high frequency subband coefficients have been corrected by using the high frequency subbands achieved by SWT of the input image....
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...That is why SWT is employed to minimize this loss....
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...The redundancy and shift invariance of the DWT mean that DWT coefficients are inherently interpolable [9]....
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...In short, SWT is similar to DWT but it does not use down-sampling, hence the subbands will have the same size as the input image....
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...This work proposed an image resolution enhancement technique based on the interpolation of the high frequency subbands obtained by DWT, correcting the high frequency subband estimation by using SWT high frequency subbands, and the input image....
[...]