scholarly journals Hybrid Sharpening Transformation Approach for Multifocus Image Fusion Using Medical and Nonmedical Images

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Sarwar Shah Khan ◽  
Muzammil Khan ◽  
Yasser Alharbi ◽  
Usman Haider ◽  
Kifayat Ullah ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Color Image ◽  
Rapid Change ◽  
Low Frequency ◽  
Experimental Results ◽  
Discrete Wavelet ◽  
Quantitative Metrics ◽  
Transformation Approach ◽  
Novel Concept

In this study, we introduced a preprocessing novel transformation approach for multifocus image fusion. In the multifocus image, fusion has generated a high informative image by merging two source images with different areas or objects in focus. Acutely the preprocessing means sharpening performed on the images before applying fusion techniques. In this paper, along with the novel concept, a new sharpening technique, Laplacian filter + discrete Fourier transform (LF + DFT), is also proposed. The LF is used to recognize the meaningful discontinuities in an image. DFT recognizes that the rapid change in the image is like sudden changes in the frequencies, low-frequency to high-frequency in the images. The aim of image sharpening is to highlight the key features, identifying the minor details, and sharpen the edges while the previous methods are not so effective. To validate the effectiveness the proposed method, the fusion is performed by a couple of advanced techniques such as stationary wavelet transform (SWT) and discrete wavelet transform (DWT) with both types of images like grayscale and color image. The experiments are performed on nonmedical and medical (breast medical CT and MRI images) datasets. The experimental results demonstrate that the proposed method outperforms all evaluated qualitative and quantitative metrics. Quantitative assessment is performed by eight well-known metrics, and every metric described its own feature by which it is easily assumed that the proposed method is superior. The experimental results of the proposed technique SWT (LF + DFT) are summarized for evaluation matrices such as RMSE (5.6761), PFE (3.4378), MAE (0.4010), entropy (9.0121), SNR (26.8609), PSNR (40.1349), CC (0.9978), and ERGAS (2.2589) using clock dataset.

scholarly journals Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Discrete Wavelet ◽  
Evaluation Indexes ◽  
Fused Image ◽  
Focus Image

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

Wavelet Transform with a Novel Integration Technique for Image Fusion

2011 ◽  
Vol 204-210 ◽  
pp. 1419-1422 ◽  
Author(s):  
Yong Yang
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
High Frequency ◽  
Low Frequency ◽  
Experimental Results ◽  
Integration Technique ◽  
Frequency Bands ◽  
Fusion Methods ◽  
Fusion Scheme ◽  
Measures Of Performance

Image fusion is to combine several different source images to form a new image by using a certain method. Recent studies show that among a variety of image fusion algorithms, the wavelet-based method is more effective. In the wavelet-based method, the key technique is the fusion scheme, which can decide the final fused result. This paper presents a novel fusion scheme that integrates the wavelet decomposed coefficients in a quite separate way when fusing images. The method is formed by considering the different physical meanings of the coefficients in both the low frequency and high frequency bands. The fused results were compared with several existing fusion methods and evaluated by three measures of performance. The experimental results can demonstrate that the proposed method can achieve better performance than conventional image fusion methods.

Hybrid Color Image Compression Using Discrete Cosine Transform and Discrete Wavelet Transform

2012 ◽  
Vol 198-199 ◽  
pp. 244-248 ◽  
Author(s):  
Ling Tang ◽  
Ming Ju Chen ◽  
Hong Song
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Discrete Wavelet Transform ◽  
Discrete Cosine Transform ◽  
Color Image ◽  
Low Frequency ◽  
Huffman Coding ◽  
Discrete Wavelet ◽  
Cosine Transform ◽  
Color Image Compression

In this research we undertake a study of image compression based on the discrete cosine transform(DCT) and discrete wavelet transform(DWT). Then a hybrid color image compression algorithm based on DCT and DWT is proposed. This algorithm is implemented through transform the color image using DWT in the YCbCr space first, and then DCT in the low frequency, adopt huffman coding, RLE and arithmetic coding in the encoded mode. In experiments, the results outperform the only DCT and the only DWT typically higher in peak signal-to-noise ratio and have better visual quality.

A Wavelet-Based Digital Watermarking Algorithm for Packaging Security

2012 ◽  
Vol 200 ◽  
pp. 660-665
Author(s):  
Shi Wei Liu ◽  
Zhen Liu ◽  
Qing Bao Wei
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Digital Watermarking ◽  
Color Image ◽  
Digital Watermark ◽  
Jpeg Compression ◽  
Experimental Results ◽  
Discrete Wavelet ◽  
Point To Point ◽  
Watermark Algorithm

In this paper, a wavelet-based digital watermark algorithm for packaging security is proposed. In the algorithm, digital watermark is embedded in the color image CMYK mode, the method based on the discrete wavelet transform (DWT) can point to point semi-adaptive repeated embed digital watermark. Digital watermark that embedded in a color image can be extracted after printing, scanning and pre-processing the color image. The experimental results show that watermark extraction’s effect is acceptable, so the algorithm can achieve the purpose of the anti-counterfeiting for packaging printing. In addition the algorithm is robust enough against various kinds of attacks such as salt&pepper noise addition, JPEG compression, image crop and so on.

A NOVEL IMAGE FUSION APPROACH BASED ON WAVELET TRANSFORM AND FUZZY LOGIC

2006 ◽  
Vol 04 (04) ◽  
pp. 617-626 ◽  
Author(s):  
TAO LI ◽  
JIAN LIU ◽  
ZHICHENG WANG ◽  
YAN TIAN
Keyword(s):  
Fuzzy Logic ◽  
Wavelet Transform ◽  
Image Fusion ◽  
Spatial Information ◽  
Low Frequency ◽  
Average Energy ◽  
Frequency Component ◽  
Discrete Wavelet ◽  
Fusion Procedure ◽  
Fusion Approach

Better understanding of the real world can be obtained by fusion of images with complementary information. It was shown that an image fusion technique based on wavelet decomposition seems to be a better trade-off between spectral and spatial information in a single image. This paper presents a novel image fusion scheme that is based on wavelet transform and fuzzy logic. The two source images are first decomposed using the discrete wavelet transformation (DWT). Then different rules are used for different components in the fusion procedure. Local average energy is utilized as the fusion parameter for the low frequency component first; then membership degree of wavelet transform coefficient is used as the fusion parameter for the high frequency parts; finally, the fused image is obtained by taking inverse wavelet transform from the combined coefficients. The proposed fusion approach is shown to be effective using some remote sensing test images.

scholarly journals An innovative image fusion algorithm based on wavelet transform and discrete fast curvelet transform

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
T. Sumathi ◽  
M. Hemalatha
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Curvelet Transform ◽  
Relevant Information ◽  
Good Time ◽  
Discrete Wavelet ◽  
Fusion Algorithm ◽  
Time Frequency ◽  
Fused Image

AbstractImage fusion is the method of combining relevant information from two or more images into a single image resulting in an image that is more informative than the initial inputs. Methods for fusion include discrete wavelet transform, Laplacian pyramid based transform, curvelet based transform etc. These methods demonstrate the best performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. In particular, wavelet transform has good time-frequency characteristics. However, this characteristic cannot be extended easily to two or more dimensions with separable wavelet experiencing limited directivity when spanning a one-dimensional wavelet. This paper introduces the second generation curvelet transform and uses it to fuse images together. This method is compared against the others previously described to show that useful information can be extracted from source and fused images resulting in the production of fused images which offer clear, detailed information.

DEPSO With DTCWT Algorithm for Multimodal Medical Image Fusion

2021 ◽  
Vol 12 (4) ◽  
pp. 78-97
Author(s):  
Hassiba Talbi ◽  
Mohamed-Khireddine Kholladi
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
High Frequency ◽  
Medical Image ◽  
Low Frequency ◽  
Weighted Average ◽  
Optimization Method ◽  
Absolute Maximum ◽  
Complex Wavelet Transform ◽  
Medical Image Fusion

In this paper, the authors propose an algorithm of hybrid particle swarm with differential evolution (DE) operator, termed DEPSO, with the help of a multi-resolution transform named dual tree complex wavelet transform (DTCWT) to solve the problem of multimodal medical image fusion. This hybridizing approach aims to combine algorithms in a judicious manner, where the resulting algorithm will contain the positive features of these different algorithms. This new algorithm decomposes the source images into high-frequency and low-frequency coefficients by the DTCWT, then adopts the absolute maximum method to fuse high-frequency coefficients; the low-frequency coefficients are fused by a weighted average method while the weights are estimated and enhanced by an optimization method to gain optimal results. The authors demonstrate by the experiments that this algorithm, besides its simplicity, provides a robust and efficient way to fuse multimodal medical images compared to existing wavelet transform-based image fusion algorithms.

scholarly journals Fusion of Medical Images in Wavelet Domain: A Discrete Mathematical Model

2018 ◽  
Vol 14 (25) ◽  
pp. 1-11
Author(s):  
Satya Prakash Yadav ◽  
Sachin Yadav
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Image Fusion ◽  
Data Transfer ◽  
Discrete Wavelet ◽  
Related Information ◽  
Medical Domain ◽  
Discrete Mathematical Model ◽  
Treatment Procedures

Introduction: Image compression is a great instance for operations in the medical domain that leads to better understanding and implementations of treatment, especially in radiology. Discrete wavelet transform (dwt) is used for better and faster implementation of this kind of image fusion.Methodology: To access the great feature of mathematical implementations in the medical domain we use wavelet transform with dwt for image fusion and extraction of features through images.Results: The predicted or expected outcome must help better understanding of any kind of image resolutions and try to compress or fuse the images to decrease the size but not the pixel quality of the image.Conclusions: Implementation of the dwt mathematical approach will help researchers or practitioners in the medical domain to attain better implementation of the image fusion and data transmission, which leads to better treatment procedures and also decreases the data transfer rate as the size will be decreased and data loss will also be manageable.Originality: The idea of using images may decrease the size of the image, which may be useful for reducing bandwidth while transmitting the images. But the thing here is to maintain the same quality while transmitting data and also while compressing the images.Limitations: As this is a new implementation, if we have committed any mistakes in image compression of medical-related information, this may lead to treatment faults for the patient. Image quality must not be reduced with this implementation.

Real-Time Vehicle License Plate Recognition Based on Scanning and 2D Haar Discrete Wavelet Transform

2013 ◽  
Vol 284-287 ◽  
pp. 2402-2406 ◽  
Author(s):  
Rong Choi Lee ◽  
King Chu Hung ◽  
Huan Sheng Wang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Real Time ◽  
Recognition Rate ◽  
Low Frequency ◽  
Experimental Result ◽  
Discrete Wavelet ◽  
License Plate ◽  
License Plate Recognition ◽  
Image Pixels

This thesis is to approach license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and artificial neural network. This thesis consists of three main parts. The first part is to locate and extract the license-plate. The second part is to train the license-plate. The third part is to real time scan recognition. We select only after the second 2D Haar Discrete Wavelet Transform the image of low-frequency part, image pixels into one-sixteen, thus, reducing the image pixels and can increase rapid implementation of recognition and the computer memory. This method is to scan for car license plate recognition, without make recognition of the individual characters. The experimental result can be high recognition rate.

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