The Experts below are selected from a list of 147 Experts worldwide ranked by ideXlab platform

Hatice Koc - One of the best experts on this subject based on the ideXlab platform.

  • A High-Dynamic-Range-Based Approach for the Display of Hyperspectral Images
    IEEE Geoscience and Remote Sensing Letters, 2014
    Co-Authors: Sarp Erturk, Secil Suer, Hatice Koc
    Abstract:

    This letter presents a new approach for hyperspectral Image visualization based on high-dynamic-range (HDR) Image processing. The proposed approach is inspired by techniques that are used to display HDR Images on low-dynamic-range media by reducing the contrast, yet preserving the Image Detail. This is the first time this concept is utilized for the display of hyperspectral Images. In the presented approach, an edge-preserving filter, called the bilateral filter, is used to extract the base and Detail Images, and the final Image is reconstructed by reducing contrast in the base Image but preserving the Detail, so that the significance of the Detail Image is enhanced. It is shown that the proposed approach improves the visual appearance and perceived Detail of hyperspectral Images.

Gang Liu - One of the best experts on this subject based on the ideXlab platform.

  • FUSION - Multi-sensor Image fusion based on fourth order partial differential equations
    2017 20th International Conference on Information Fusion (Fusion), 2017
    Co-Authors: Durga Prasad Bavirisetti, Gang Xiao, Gang Liu
    Abstract:

    In this paper, a new Image fusion algorithm based on fourth order partial differential equations and principal component analysis is introduced. This is for the first time fourth order partial differential equations brought into the context of Image fusion. The proposed algorithm is as follows: First, fourth order partial differential equations are applied on each source Image to obtain approximation and Detail Images. Second, principal component analysis is applied on Detail Images to obtain optimal weights. Third, final Detail Image is obtained by fusing these Detail Images with help of optimal weights. Fourth, final approximation Image is obtained by employing an average operation on approximation Images. Finally, resultant fused Image is calculated by combining the final approximation and Detail Images. Experiments are conducted on standard fusion datasets. Results are analyzed with help of petrovic metrics and further compared with traditional and recent fusion methods. Results justify that performance of the proposed method is superior to state-of-the-art fusion methods. Moreover, reasonable computational time, easy and effective implementation of the proposed method makes it suitable for real time applications.

Sarp Erturk - One of the best experts on this subject based on the ideXlab platform.

  • A High-Dynamic-Range-Based Approach for the Display of Hyperspectral Images
    IEEE Geoscience and Remote Sensing Letters, 2014
    Co-Authors: Sarp Erturk, Secil Suer, Hatice Koc
    Abstract:

    This letter presents a new approach for hyperspectral Image visualization based on high-dynamic-range (HDR) Image processing. The proposed approach is inspired by techniques that are used to display HDR Images on low-dynamic-range media by reducing the contrast, yet preserving the Image Detail. This is the first time this concept is utilized for the display of hyperspectral Images. In the presented approach, an edge-preserving filter, called the bilateral filter, is used to extract the base and Detail Images, and the final Image is reconstructed by reducing contrast in the base Image but preserving the Detail, so that the significance of the Detail Image is enhanced. It is shown that the proposed approach improves the visual appearance and perceived Detail of hyperspectral Images.

Meie Fang - One of the best experts on this subject based on the ideXlab platform.

  • An adaptive two-scale biomedical Image fusion method with statistical comparisons
    Computer Methods and Programs in Biomedicine, 2020
    Co-Authors: Meie Fang
    Abstract:

    Abstract Two-scale Image representation of base and Detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of Image fusion. Unfortunately, for a pseudo-colour input Image, the base and Detail Images in the spatial-domain obtained via Image decomposition scheme always display in greyscale. In this paper, a two-scale Image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour Image in the colour space domain. For greyscale Image, Detail and base Image are obtained using structural information extracted from the difference Image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and Detail Image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical Image and protein Image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data.

M. N. Giri Prasad - One of the best experts on this subject based on the ideXlab platform.

  • ICCCNT - A New Hybrid Medical Image Fusion Method Based on Fourth-Order Partial Differential Equations Decomposition and DCT in SWT domain
    2019 10th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2019
    Co-Authors: K. Vanitha, D. Satyanarayana, M. N. Giri Prasad
    Abstract:

    In this paper, a new hybrid method based on fourth-order partial differential equations (FPDE) and discrete cosine transform (DCT) in stationary wavelet transform (SWT) domain is proposed for fusing the multimodality Images such as CT and MRI. First, the input Images are decomposed into base and Detail Images using fourth-order differential equations method. Final Detail Image is obtained by weighted average of principal components of Detail Images. Next, the base Images are given as input for SWT decomposition. The corresponding four subband coefficients are processed using DCT. DCT is used to extract significant Details of the subband coefficients. Spatial frequency of each coefficient is calculated to improve the extracted features. At last, fusion rule is used to fuse DCT coefficient's based on spatial frequency value. Final base Image is obtained by applying inverse DCT and inverse SWT. By combining the above final Detail and base Images linearly, a final fused Image is generated. The comparative analysis of proposed method with the existing fusion algorithms is carried out. From the results it is observed that proposed method gives better performance in terms of objective criteria like mean, STD, MI, FMI, etc., than the existing methods.