Multi-resolution image fusion technique and its application to forensic science

Wen, Che‐Yen; Chen, J.K.

doi:10.1016/j.forsciint.2003.11.034

Cited by 60 publications

(30 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…So, various alternatives are compared in this paper, which are as follows: 1) Averaging fusion rule for low-frequency subimages, and for high-frequency subimages: a) maximum-selection fusion rule is used to select the pixel with larger absolute value [13]. b) The pixel from a source image having larger standard variance calculated based on its 3×3 neighbors is used to be the value in the fused image in the same location [14]. c) The pixel from a source image having larger energy calculated based on its 3×3 neighbors is used to be the value in the fused image in the same location [15].…”

Section: B Comparison Of Different Fusion Rulesmentioning

confidence: 99%

A Comparative Study of Wavelet-Based Image Fusion with a Novel Fusion Rule

Jiang¹,

Zhang²,

Zhang³

2015

IJMLC

View full text Add to dashboard Cite

Abstract-Image fusion is the process of combining information of interest in two or more images of a scene into a single highly informative image. Generally, the multi-resolution image fusion based on the wavelet transform performs better on diverse images than traditional methods. Therefore, a comparative study of wavelet-based image fusion with different wavelet families and fusion methods are far-reaching to guide people in their applications. On the other hand, in this paper, a novel fusion rule based on focus measure and local contrast measure is proposed to analyze the information in images and help selecting appropriate information from different source images to obtain a fused image. Experimental results on various wavelet functions and fusion rules demonstrate that the proposed fusion approach outperforms traditional methods in real images.Index Terms-Fusion rule, image fusion, local contrast measure, wavelet transform.

show abstract

Section: B Comparison Of Different Fusion Rulesmentioning

confidence: 99%

A Comparative Study of Wavelet-Based Image Fusion with a Novel Fusion Rule

Jiang¹,

Zhang²,

Zhang³

2015

IJMLC

View full text Add to dashboard Cite

show abstract

“…Image fusion over the years has become a useful technique in the remote sensing field, not only making the interpretation process faster and more reliable, but also providing unique and accurate information for the extracted features (Wen & Chen 2004). There are distinct advantages of fusing radar with optical data, as the end product has the advantage of spatial information (radar image texture) and spectral information from the optical and infrared bands.…”

Section: Research Objectivesmentioning

confidence: 99%

Optical and radar data comparison and integration: Kenya example

Sheoran¹,

Haack

2013

Geocarto International

View full text Add to dashboard Cite

The purpose of this study was to evaluate the relative classification accuracies of four land covers/uses in Kenya using spaceborne quad polarization radar from the Japanese ALOS PALSAR system and optical Landsat Thematic Mapper data. Supervised signature extraction and classification (maximum likelihood) was used to classify the different land covers/uses followed by an accuracy assessment. The original four band radar had an overall accuracy of 77%. Variance texture was the most useful of four measures examined and did improve overall accuracy to 80% and improved the producer's accuracy for urban by almost 25% over the original radar. Landsat provided a higher overall classification accuracy (86%) as compared to radar. The merger of Landsat with the radar texture did not increase overall accuracy but did improve the producer's accuracy for urban indicated some advantages for sensor integration. IntroductionAssessing many problems within environmental studies, economic planning, resource management, restoration projects and disaster preparedness requires a scientific analysis of data using processes available within the geospatial industry. With the launch of recent spaceborne radar systems, including RADARSAT-2, ALOS PALSAR and TerraSAR-X, the application and use of now operationally available quad polarization radar data for spatial information may prove beneficial for multiple situations. However, the potential of quad polarization radar data for land cover/use classification and other applications remains in its early stages as a result of previously limited data availability and analysis. Only with more examination of these relatively new spaceborne quad polarization data can the scientific and application community maximize the potential benefits of these technological innovations.Traditional means of providing reliable land cover/use information has been primarily undertaken by multispectral systems such as Landsat Thematic Mapper (TM). These systems, because of their limited functionality in cloud covered areas, are not able to fully sustain the demands for providing land cover/use information for many areas around the world. However, with the success of RADARSAT-1 and other spaceborne radar systems, this limitation has been addressed to a certain extent.

show abstract

“…As many kinds of electro-optical trackers are widely used in various fields, image fusion becomes a significantly meaningful technique. Many researchers [2][3][4][5][6][7][8] have contributed their efforts to the problem and developed a number of practical algorithms in recent years. However, most of the approaches are designed for intensity images, not for color images.…”

Section: Introductionmentioning

confidence: 99%