CHANGE DETECTION FOR HYPERSPECTRAL IMAGES USING EXTENDED MUTUAL INFORMATION AND OVERSEGMENTATION

Date

2018-09-23

Author

TASKESEN, BAHAR
KOZ, ALPER
Weatherbee, Oliver
Alatan, Abdullah Aydın

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

102
views

0
downloads

We propose a change detection algorithm for hyperspectral images by properly extending the description of commonly used mutual information metric in monochrome images to hyperspectral images. The newly extended metric for the additional spectral dimension in hyperspectral images accumulates the effects of all spectral hands to the statistical relation between the pixels of the two images at the same location. In order to avoid blurring kind of distortions in the change maps resulting from the usage of fixed size kernels during the calculation of mutual information in previous literature, the proposed method first applies an oversegmentation to the hyperspectral images and then, computes the extended metric over the produced superpixels. The proposed approach based on joint superpixels and extended mutual information is compared with two basic approaches, whereas the first one uses conventional mutual information of two images and the second method utilizes the extended mutual information over rectangular kernels. The experimental results indicate that the change masks obtained by the proposed method are more accurate compared to the baseline approaches.

URI

https://hdl.handle.net/11511/36938

DOI

https://doi.org/10.1109/whispers.2018.8747018

Conference Name

9th Workshop on Hyperspectral Image and Signal Processing - Evolution in Remote Sensing (WHISPERS)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Sensor Fusion of a Camera and 2D LIDAR for Lane Detection Schmidt, Klaus Verner (null; 2019-04-26) This paper presents a novel lane detection algorithm based on fusion of camera and 2D LIDAR data. On the one hand, objects on the road are detected via 2D LIDAR. On the other hand, binary bird’s eye view (BEV) images are acquired from the camera data and the locations of objects detected by LIDAR are estimated on the BEV image. In order to remove the noise generated by objects on the BEV, a modified BEV image is obtained, where pixels occluded by the detected objects are turned into background pixels. Then,...
Anlık Spektral Görüntüleme için Tasarım Eniyileme Ayazgök, Suleyman; Öktem, Sevinç Figen (2019-08-22) Snapshot spectral imaging enables to reconstructspectral images from a multiplexed single-shot measurement.Since an inversion is required to form the spectral images com-putationally, quantitative characterization of their performanceis essential to optimize the design. In this paper, we analyze theoptimal design of a snapshot spectral imaging technique. Thissnapshot multi-spectral imaging technique uses a diffractive lenscalled generalized photon sieve, and vari...
Efficient algorithms for convolutional inverse problems in multidimensional imaging Doğan, Didem; Öktem, Figen S.; Department of Electrical and Electronics Engineering (2020) Computational imaging is the process of indirectly forming images from measurements using image reconstruction algorithms that solve inverse problems. In many inverse problems in multidimensional imaging such as spectral and depth imaging, the measurements are in the form of superimposed convolutions related to the unknown image. In this thesis, we first provide a general formulation for these problems named as convolutional inverse problems, and then develop fast and efficient image reconstruction algorith...
Shape recognition with generalized beam angle statistics Tola, OO; Arica, N; Yarman-Vural, F (2004-01-01) In this study, we develop a new shape descriptor and a matching algorithm in order to find a given template shape in an edge detected image without extracting the boundary. The shape descriptor based on Generalized Beam Angle Statistics (GBAS) defines the angles between the lines connecting each boundary point with the rest of the points, as random variable. Then, it assigns a feature vector to each point using the moments of beam angles. The proposed matching algorithm performs shape recognition by matchin...
GPS-Based Real-Time Orbit Determination of Low Earth Orbit Satellites Using Robust Unscented Kalman Filter Karslıoğlu, Mahmut Onur; Erdogan, Eren; Pamuk, Onur (2017-11-01) In this research, a novel algorithm for real-time orbit determination (RTOD) is presented using the robust unscented Kalman filter (RUKF) with global positioning system (GPS) group and phase ionospheric correction (GRAPHIC) observables. To increase the reliability of the solution, a robust approach is included in the UKF to cope with the bad, invalid, or degraded measurements leading to the divergence or inaccurate output of the filter. Robustness is provided by making the filter less sensitive to faulty me...

Citation Formats

B. TASKESEN, A. KOZ, O. Weatherbee, and A. A. Alatan, “CHANGE DETECTION FOR HYPERSPECTRAL IMAGES USING EXTENDED MUTUAL INFORMATION AND OVERSEGMENTATION,” presented at the 9th Workshop on Hyperspectral Image and Signal Processing - Evolution in Remote Sensing (WHISPERS), Amsterdam, Netherlands, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36938.