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Full-Text Articles in Engineering
A New Effective Denoising Filter For High Density Impulse Noise Reduction, Iman Elawady, Caner Özcan
A New Effective Denoising Filter For High Density Impulse Noise Reduction, Iman Elawady, Caner Özcan
Turkish Journal of Electrical Engineering and Computer Sciences
Today, thanks to the rapid development of technology, the importance of digital images is increasing. However, sensor errors that may occur during the acquisition, interruptions in the transmission of images and errors in storage cause noise that degrades data quality. Salt and pepper noise, a common impulse noise, is one of the most well-known types of noise in digital images. This noise negatively affects the detailed analysis of the image. It is very important that pixels affected by noise are restored without loss of image fine details, especially at high level of noise density. Although many filtering algorithms have been …
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 …
Detection Of Seagrass Scars Using Sparse Coding And Morphological Filter, Ender Oguslu, Sertan Erkanli, Victoria J. Hill, W. Paul Bissett, Richard C. Zimmerman, Jiang Li, Charles R. Bostater Jr. (Ed.), Stelios P. Mertikas (Ed.), Xavier Neyt (Ed.)
Detection Of Seagrass Scars Using Sparse Coding And Morphological Filter, Ender Oguslu, Sertan Erkanli, Victoria J. Hill, W. Paul Bissett, Richard C. Zimmerman, Jiang Li, Charles R. Bostater Jr. (Ed.), Stelios P. Mertikas (Ed.), Xavier Neyt (Ed.)
OES Faculty Publications
We present a two-step algorithm for the detection of seafloor propeller seagrass scars in shallow water using panchromatic images. The first step is to classify image pixels into scar and non-scar categories based on a sparse coding algorithm. The first step produces an initial scar map in which false positive scar pixels may be present. In the second step, local orientation of each detected scar pixel is computed using the morphological directional profile, which is defined as outputs of a directional filter with a varying orientation parameter. The profile is then utilized to eliminate false positives and generate the final …
Fast Stochastic Wiener Filter For Super-Resolution Image Restoration With Information Theoretic Visual Quality Assessment, Amr Hussein Yousef, Jiang Li, Mohammad Karim, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)
Fast Stochastic Wiener Filter For Super-Resolution Image Restoration With Information Theoretic Visual Quality Assessment, Amr Hussein Yousef, Jiang Li, Mohammad Karim, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)
Electrical & Computer Engineering Faculty Publications
Super-resolution (SR) refers to reconstructing a single high resolution (HR) image from a set of subsampled, blurred and noisy low resolution (LR) images. The reconstructed image suffers from degradations such as blur, aliasing, photo-detector noise and registration and fusion error. Wiener filter can be used to remove artifacts and enhance the visual quality of the reconstructed images. In this paper, we introduce a new fast stochastic Wiener filter for SR reconstruction and restoration that can be implemented efficiently in the frequency domain. Our derivation depends on the continuous-discrete-continuous (CDC) model that represents most of the degradations encountered during the image-gathering …
Mathematical Model Development Of Super-Resolution Image Wiener Restoration, Amr H. Yousef, Jiang Li, Mohammad A. Karim
Mathematical Model Development Of Super-Resolution Image Wiener Restoration, Amr H. Yousef, Jiang Li, Mohammad A. Karim
Electrical & Computer Engineering Faculty Publications
In super-resolution (SR), a set of degraded low-resolution (LR) images are used to reconstruct a higher-resolution image that suffers from acquisition degradations. One way to boost SR images visual quality is to use restoration filters to remove reconstructed images artifacts. We propose an efficient method to optimally allocate the LR pixels on the high-resolution grid and introduce a mathematical derivation of a stochastic Wiener filter. It relies on the continuous-discrete-continuous model and is constrained by the periodic and nonperiodic interrelationships between the different frequency components of the proposed SR system. We analyze an end-to-end model and formulate the Wiener filter …