Uniform Based Approach for Image Fusion

Radhika, V.; Kilari, Veeraswamy; Samayamantula, Srinivaskumar

doi:10.1007/978-3-642-32112-2_23

Cited by 4 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The multi-focus image fusion algorithms are classified into spatial and transform domain fusion methods. The spatial domain techniques [1,2] use local spatial features such as gradient, spatial frequency, and standard derivation to fuse source images. However, the spatial domain techniques introduce undesirable effects such as image blurring and contrast reduction.…”

Section: Introductionmentioning

confidence: 99%

Multifocus Color Image Fusion Based on Walsh Hadamard Transform and SumModified-Laplacian Focus Measure

Radha¹,

Babu²

2019

IJIES

View full text Add to dashboard Cite

Multi-focus image fusion objective is to add relevant information from multiple images of the same scene but with different focuses into a sharper image that is more suitable for visual sensor networks. Natural and artificially obtained multifocus color images are considered for fusion. The existing fusion methods like multi scale and multi-resolution transforms are proved to be good in Multi-focus Image Fusion. However, they suffer from computational complexity in kernels calculation. In this paper, Multi-focus color Image Fusion based on Walsh-Hadamard Transform and sum-modified-Laplacian focus measure is proposed. Walsh-Hadamard Transform is a non-sinusoidal, orthogonal transform with symmetry, seperability and orthogonal properties. These properties make it more apt for image fusion than other transforms. And the sum-modified-Laplacian focus measure helps to get sharper image. Proposed method performance is evaluated in terms of reference and non-reference measures. The experimental results indicate that proposed method not only produces sharp details in fused image but also reduces the computational complexity.

show abstract

Section: Introductionmentioning

confidence: 99%

Multifocus Color Image Fusion Based on Walsh Hadamard Transform and SumModified-Laplacian Focus Measure

Radha¹,

Babu²

2019

IJIES

View full text Add to dashboard Cite

show abstract

“…A major problem with DWT is its shift variant nature caused by sub-sampling which occur at each level. A small shift in the input signal results in a completely different distribution of energy between DWT coefficients at different scales [16][17][18][19][20][21]. To overcome the shift variant problem, block based transforms are preferred.…”

Section: Introductionmentioning

confidence: 99%

An Image Fusion Technique Based on Hadamard Transform and HVS

Radhika

Kilari²,

Kumar

2016

Eng. Technol. Appl. Sci. Res.

View full text Add to dashboard Cite

The main endeavor of image fusion is to obtain an image that contains more visual quality information than any one of the source images. In general, the source images may be multi focus, multi modality, multi resolution, multi temporal, panchromatic, satellite images considered for fusion. This paper discusses image fusion using Hadamard Transform (HT). In this work, Human Visual System (HVS) is investigated for image fusion in the HT domain. The proposed fusion process contains three important parts, (1) divide source images into sub images / blocks and transform them into HT domain. (2) multiply transformed coefficients with HVS based weightage matrix of HT and select the highest value from them (3) fuse the corresponding block of selected coefficients from source images in to an empty image. The utility of HVS makes the coefficients more significant. The performance of the proposed method is analyzed and compared with Discrete Wavelet Transform (DWT) based image fusion technique. Implementation in HT domain is simple and time saving when compared with DWT.

show abstract