Adjustable intensity-hue-saturation and Brovey transform fusion technique for IKONOS/QuickBird imagery

Tu, Te-Ming; Lee, Yuh-Chi; Chang, Chien-Ping; Huang, Ping

doi:10.1117/1.2124871

Cited by 60 publications

(39 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…One of the first modifications of the IHS method extends the IHS method from three bands to four by incorporating an infrared component (Tu et al 2005). Regarding the fact that the panchromatic sensors pick up infrared light (IR) in addition to visible wavelengths, this modification caused the intensity image to be better matched with the panchromatic image.…”

Section: Ihs Pan-sharpening Techniquementioning

confidence: 99%

“…A similar modification of IHS, called the 'Fast Intensity-HueSaturation fusion technique with Spectral Adjustment' (FIHS-SA) method, incorporates four bands with weighting coefficients on the green and blue bands to minimize the difference between intensity and the panchromatic images. These weighting coefficients were calculated experimentally a fuse IKONOS images (Tu et al 2005). In 2008 Choi expanded this work and experimentally determined the coefficients for the red and infrared bands for IKONOS images (Choi.…”

Section: Ihs Pan-sharpening Techniquementioning

confidence: 99%

See 1 more Smart Citation

A Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

Niazi

Mokhtarzade

Saeedzadeh

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Pan sharpening methods aim to produce a more informative image containing the positive aspects of both source images. However, the pan sharpening process usually introduces some spectral and spatial distortions in the resulting fused image. The amount of these distortions varies highly depending on the pan sharpening technique as well as the type of data. Among the existing pan sharpening methods, the Intensity-Hue-Saturation (IHS) technique is the most widely used for its efficiency and high spatial resolution. When the IHS method is used for IKONOS or QuickBird imagery, there is a significant color distortion which is mainly due to the wavelengths range of the panchromatic image. Regarding the fact that in the green vegetated regions panchromatic gray values are much larger than the gray values of intensity image. A novel method is proposed which spatially adjusts the intensity image in vegetated areas. To do so the normalized difference vegetation index (NDVI) is used to identify vegetation areas where the green band is enhanced according to the red and NIR bands. In this way an intensity image is obtained in which the gray values are comparable to the panchromatic image. Beside the genetic optimization algorithm is used to find the optimum weight parameters in order to gain the best intensity image. Visual and statistical analysis proved the efficiency of the proposed method as it significantly improved the fusion quality in comparison to conventional IHS technique. The accuracy of the proposed pan sharpening technique was also evaluated in terms of different spatial and spectral metrics. In this study, 7 metrics (Correlation Coefficient, ERGAS, RASE, RMSE, SAM, SID and Spatial Coefficient) have been used in order to determine the quality of the pan-sharpened images. Experiments were conducted on two different data sets obtained by two different imaging sensors, IKONOS and QuickBird. The result of this showed that the evaluation metrics are more promising for our fused image in comparison to other pan sharpening methods.

show abstract

Section: Ihs Pan-sharpening Techniquementioning

confidence: 99%

Section: Ihs Pan-sharpening Techniquementioning

confidence: 99%

A Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

Niazi

Mokhtarzade

Saeedzadeh

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…Another reason why BT is the most applicable method is such a condition is that. They add the component of brightness and intensity in the resultant fused image by performing multiplication of the result with the anticipated data [81].…”

Section: Brovey Transformationsmentioning

confidence: 99%

Image Fusion Methods: A Survey

Masood¹,

Sharif²,

Yasmin³

et al. 2017

JESTR

View full text Add to dashboard Cite

Image fusion is an approach which is used to amalgamate the corresponding features in a sequence of input images to a single composite image that preserves all the significant features of the input images. Image fusion is also known as pansharpening. It is a method which is used to integrate and add the geometric detail of a high-resolution panchromatic (Pan) image and the information of color of a low-resolution multispectral (MS) image for the production of a high-resolution MS image. This methodology is mainly most important and significant for any large-scale applications. Image fusion classification based on its systems (models and algorithms) are considered and overviewed in this survey. The basic two algorithms categories are analyzed and compared to each other, in the analysis and discussion section the major points to be considered while performing image fusion are highlighted.

show abstract

“…Some works are based on the transition to color-difference metrics of computer graphics ("color-metric methods"), where the question about decorrelation of primary data is solved (Ling, 2007, Rahmani, 2010, Thomas, 2008. The modification to the IHS method, called the IHS-SA, proposed the incorporation of weighted coefficients on the green and blue bands so as to reduce the difference between the intensity and the panchromatic bands (Tu et al, 2005). However, these methods allow us to take into account only spectral components of primary grayscale image (Vivone, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…However, the tradeoff is higher complexity and cost. Many fusion algorithms (Tu, 2005, Zhang, 2005, Zhang, 2010 were developed and tested on different commercial satellite data such as Ikonos and Quickbird, however, the efficacy of these algorithms is poorly assessed on the satellite data of Worldview-2 (Padwick, 2010). The panchromatic band of Ikonos and Quickbird ranges between 0.45 and 0.90 micrometers; the Worldview panchromatic band is narrower and ranges between 0.45 and 0.8 micrometers.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing Image Fusion Using Ica and Optimized Wavelet Transform

Hnatushenko¹,

Vasyliev²

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:In remote-sensing image processing, fusion (pan-sharpening) is a process of merging high-resolution panchromatic and lower resolution multispectral (MS) imagery to create a single high-resolution color image. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. However, the pan-sharpening image produced by these methods gets the high color distortion of spectral information. In this paper, to minimize the spectral distortion we propose a remote sensing image fusion method which combines the Independent Component Analysis (ICA) and optimization wavelet transform. The proposed method is based on selection of multiscale components obtained after the ICA of images on the base of their wavelet decomposition and formation of linear forms detailing coefficients of the wavelet decomposition of images brightness distributions by spectral channels with iteratively adjusted weights. These coefficients are determined as a result of solving an optimization problem for the criterion of maximization of information entropy of the synthesized images formed by means of wavelet reconstruction. Further, reconstruction of the images of spectral channels is done by the reverse wavelet transform and formation of the resulting image by superposition of the obtained images. To verify the validity, the new proposed method is compared with several techniques using WorldView-2 satellite data in subjective and objective aspects. In experiments we demonstrated that our scheme provides good spectral quality and efficiency. Spectral and spatial quality metrics in terms of RASE, RMSE, CC, ERGAS and SSIM are used in our experiments. These synthesized MS images differ by showing a better contrast and clarity on the boundaries of the "object of interest -the background". The results show that the proposed approach performs better than some compared methods according to the performance metrics.

show abstract

Adjustable intensity-hue-saturation and Brovey transform fusion technique for IKONOS/QuickBird imagery

Cited by 60 publications

References 9 publications

A Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

A Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

Image Fusion Methods: A Survey

Remote Sensing Image Fusion Using Ica and Optimized Wavelet Transform

Contact Info

Product

Resources

About