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Full-Text Articles in Engineering
Near Real-Time Operation Of Public Image Database For Ground Vehicle Navigation, Ehsan A. Ali, Samuel Peter Kozaitis
Near Real-Time Operation Of Public Image Database For Ground Vehicle Navigation, Ehsan A. Ali, Samuel Peter Kozaitis
Electrical Engineering and Computer Science Faculty Publications
An effective color night vision system for ground vehicle navigation should operate in near real-time to be practical. We described a system that uses a public database as a source of color information to colorize night vision imagery. Such an approach presents several problems due to differences between acquired and reference imagery. Our system performed registration, colorizing, and reference updating in near real-time in an effort to help drivers of ground vehicles during night to see a colored view of a scene.
Improved Colorization For Night Vision System Based On Image Splitting, Ehsan A. Ali, Samuel Peter Kozaitis
Improved Colorization For Night Vision System Based On Image Splitting, Ehsan A. Ali, Samuel Peter Kozaitis
Electrical Engineering and Computer Science Faculty Publications
The success of a color night navigation system often depends on the accuracy of the colors in the resulting image. Often, small regions can incorrectly adopt the color of large regions simply due to size of the regions. We presented a method to improve the color accuracy of a night navigation system by initially splitting a fused image into two distinct sections before colorization. We split a fused image into two sections, generally road and sky regions, before colorization and processed them separately to obtain improved color accuracy of each region. Using this approach, small regions were colored correctly when …
Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li
Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li
Electrical & Computer Engineering Faculty Publications
We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l1/lq regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …