Multi-focus image fusion using variance based spatial domain and Wavelet Transform

Sahoo, Tapasmini; Mohanty, Sankalp; Sahu, Saurav Kumar

doi:10.1109/mspct.2011.6150517

Cited by 9 publications

(3 citation statements)

References 11 publications

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“…The proposed method is tested on artificial, natural and misregistered multi-focus images. The proposed method performance is compared with existing DWT [3], MSVD [6], SWT [8], DWT + Variance [9], and DTCWT [10] fusion methods in terms of performance measures.…”

Section: Resultsmentioning

confidence: 99%

“…The fusion techniques using Laplacian pyramids [2], Discrete Wavelet Transform (DWT) [3], discrete cosine transform [4], Walsh Hadamard Transform [5], multiresolution singular value decomposition (MSVD) [6], Wavelet based methods [7][8][9][10][11][12] are existing in the literature. The discrete wavelet transform (DWT) based method had been verified to be an effective image fusion technique.…”

Section: Literature Reviewmentioning

confidence: 99%

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Stationary Wavelet Transform based Image Fusion using fusion rules

Radha,

Babu

2019

IJEAT

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Multifocus image fusion is a current research topic in the area of image processing for visual sensor networks. Discrete wavelet transform based fusion algorithms suffer from unintended effects like smoothing of edges, loss of contrast and artifacts. To overcome these problems, Stationary Wavelet Transform based algorithm using fusion-rules is proposed and applied to multifocus images. Stationary Wavelet Transform well preserves the edges and avoid artifacts with its shift-invariance property. Entropy and spatial frequency based fusion rules in this work can effectively characterize the intensity variations in an image there by loss of contrast is minimized. Simulation results show that the proposed method can amply preserve the edges and also avoid artifacts with no loss of contrast.

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Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Stationary Wavelet Transform based Image Fusion using fusion rules

Radha,

Babu

2019

IJEAT

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“…The output contains the information of the two decomposed or source images. The decomposition is done because to get the accuracy in source image that is we are filtering or eliminating unwanted coefficients which are detailed coefficients [10,13]. Mainly it takes three steps to perform fusion [14] Step 1: Firstly decompose the two source images to get lower decomposed images.…”

Section: Image Fusionmentioning

confidence: 99%

Image enhancement with contrast coefficients using wavelet based image fusion

Pardhasaradhi¹,

PMadhav²,

Sindhuja³

et al. 2018

IJET

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The future is mainly focused on image brightness and the capacity that required storing the image. The sharp images provide better information than the blur images. To overcome from the blurriness in the image, we use image enhancement techniques. Image fusion used to overcome information loss in the image. This paper is provided with image enhancement and fusion by applying wavelet transform technique. Wavelet transform is mainly used because due to its inherent property that is they are redundant and shift invariant. It transforms the image into different scales. Image enhancement will be decided based on the levels of transformation. Low contrast results from poor resolution, lack of dynamic range, wrong settings of sensor lens during acquisition and poor quality of cameras and sensors. To avoid the information loss there is an interesting solution that is for the pictures of the same image but focused on different regions. Then using image fusion concept, all images which are captured are combined to get a single image which contains the properties of both the source images. The image entropy is composed to determine the quality of the image. The paper shows the image fusion method for both multi-resolution and images captured at different temperatures.

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Euclidian Norm Based Fusion Strategy for Multi Focus Images

Shihabudeen¹,

Rajeesh²

2021

2021 2nd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS)

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Multi-focus image fusion using variance based spatial domain and Wavelet Transform

Cited by 9 publications

References 11 publications

Stationary Wavelet Transform based Image Fusion using fusion rules

Stationary Wavelet Transform based Image Fusion using fusion rules

Image enhancement with contrast coefficients using wavelet based image fusion

Euclidian Norm Based Fusion Strategy for Multi Focus Images

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