Image Resolution Enhancement using Multi-wavelet Transforms with Interpolation Technique (original) (raw)

Image Resolution Enhancement by Wavelet Transform

Abstract— Wavelet transform based images resolution improvement is new technique in which all low and high frequency bands are considered for improvement using interpolation techniques like linear and bicubic which scales image. In previous work only high frequency bands are used for interpolation here differently low pass band is also considered because LL low –low frequency band mainly consist directional information feature .The interpolated frequency sub band coefficients have been corrected by using the frequency sub bands achieved by SWT of the input image. An original image is interpolated with half of the interpolation factor used for interpolation the high frequency sub bands. Afterwards all these images have been combined using IDWT to generate super resolved image. We are interpolating it to achieve high resolution using directional information features of low low band. We are using the input image for the interpolation of low frequency sub band image.

Image Resolution Enhancement using DWT and Spatial Domain Interpolation Technique

Image Resolution is one of the important quality metrics of images. Images with high resolution are required in many fields. In this paper, a new resolution enhancement technique is proposed based on the interpolation of four sub band images generated by Discrete Wavelet Transform (DWT) and the original Low Resolution (LR) input image. In this technique, the four sub band images generated by DWT and the input LR image are interpolated with scaling factor, α and then performed inverse DWT to obtain the intermediate High Resolution (HR) Image. The difference between the intermediate HR image and the interpolated LR input image is added to the intermediate HR image to obtain final output HR Image. Lanczos interpolation is used in this technique. The proposed technique is tested on well known bench mark images. The quantitative and visual results shows the superiority of the proposed technique over the conventional and state of art image resolution enhancement techniques in wavelet domain using haar wavelet filter.

IMAGE RESOLUTION ENHANCEMENT BY USING WAVELET TRANSFORM-2

NOW day's resolution of image is an important issue in almost all image and video processing applications like, feature extraction, video resolution enhancement, and satellite image resolution enhancement. Satellite images are used in various applications like geoscientific studies, astronomy, and geographical information systems.

Image resolution enhancement using multi-wavelet and cycle-spinning

Proceedings of 2012 UKACC International Conference on Control, 2012

Images with high resolution give better results for image processing applications. Image resolution enhancement is the process of manipulating an image so that resultant image is more suitable for specific application such as medical, agricultural, satellite image processing. This paper is based on image resolution enhancement by combination of SWT & DWT .In DWT main loss is on high frequency components. The edge loss in high frequency components of DWT is minimized by adding it with high frequency components of SWT which is transition invariant transform. The interpolated high frequency sub-bands of DWT are added with high frequency sub bands of SWT. Then the added high frequency sub-bands (of SWT & DWT) as well as the input image are interpolated by factor of α/2to enlarge the input image by factor of α. Afterwards all these images have been combined using IDWT to generate a super resolved image. Algorithm considering Haar function is developed for DWT & inverse IDWT instead of using db9/7. This obtained image is compared with original high resolution image. This technique has been tested on standard bench mark images. The quantitative (Peak signal to noise ratio) and visual results are superior over conventional image resolution enhancement techniques.

DESIGN OF IMAGE RESOLUTION ENHANCEMENT BY USING DWT AND SWT

IRJET, 2019

Now a day resolution of image is an important issue in almost all image and video processing applications. An image resolution enhancement technique is based on interpolation. In picture dispensation to increase number of pixels in digital image is called as interpolation. The Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) are applied on the input image and these techniques are applied to decompose an image into high frequency sub bands. DWT is applied in instruct to decompose an input image into dissimilar sub bands. Then the elevated frequency sub bands as well as the input image are interpolated. By using SWT technique the estimated high frequency sub bands to generate a new high resolution image by using Inverse Discrete Wavelet Transform.

Comparision of different Image Resolution Enhancement techniques using wavelet transform

—We propose an Image resolution enhancement techniques based on interpolation of the high frequency subband images obtained from wavelet zero padding-cycle spinning, discrete, stationary and Dual tree Complex wavelet transform (DT-CWT). In this study, a comparison of three different image resolution enhancement techniques in wavelet domain is done. Each method is analyzed quantitatively and visually. Based on the analysis, the most efficient method is proposed. All the three algorithms uses low resolution image as the input image and then wavelet transform is applied to decompose the input image into different high and low frequency subbands. Then these subband images along with the input image are interpolated. Finally all these images are combined to generate a new resolution enhanced image by using inverse process. Keywords— wavelet zero padding, discrete wavelet transform, stationary wavelet transform, Dual tree complex wavelet transform, interpolation.

IMAGE RESOLUTION ENHANCEMENT USING WAVELET DECOMPOSITION

Satellite images are being used in many fields of research. One of the major issues of these types of images is theirresolution.In this correspondence, I propose an image resolution enhancement technique based on interpolation of the high frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different subbands. Then the high frequency subbands as well as the input image are interpolated. The estimated high frequency subbands are being modified using high frequency subbands obtained through SWT. Then all these subbands are combined to generate a new high resolution image using inverse DWT (IDWT). The quantitative and visual results are showing the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. KEYWORDS: Discrete wavelet transform (DWT), Sationary Wavelet transform (SWT), interpolation, satellite image resolution enhancement, wavelet zero padding (WZP).

A Novel Method For Image Enhancement By Using SWT And DWT

Eighth Sense Research Group

Abstract — an image resolution enhancement technique based on interpolation of the high frequency sub band images obtained by discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different sub bands. DWT has been employed in order to preserve the high frequency components of the image. The redundancy and shift invariance of the DWT mean that DWT coefficients are inherently interpolable. Then the high frequency sub bands as well as the input image are interpolated. The estimated high frequency sub bands are being modified by using high frequency sub band obtained through SWT. Then all these sub bands are combined to generate a new high resolution image by using inverse DWT (IDWT). Index Terms—Discrete wavelet transform, image super resolution, stationary wavelet transform.

Wavelet Based Various Interpolation Techniques for High Resolution Image Enhancement Processing

Satellite images are used in many fields of Earth Science Research and development. One of the main concepts of these types of images is their resolution. In this paper, we propose a hybrid satellite image resolution enhancement technique based on the image pixels values. The high-frequency content sub band's images are obtained by the implementing SWT and DWT of the input image. In this technique the input image is decomposed into different sub band's content images like LL, LH, HL and HH from this four different sub band's images combined with low-resolution input image have been interpolated, followed by combining all these images to generate a new high resolution-enhanced image by using IDWT. In this way to achieve a high resolution image, an intermediate stage for estimating the high-frequency subbands has been interpolated and proposed. This proposed technique has been tested on different low resolution satellite benchmark images. The image quantitative to be analysis the PSNR, MSE, RMSE and entropy show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques.