IEEE 2015 Matlab based Image Processing

Automatic Construction of 3-D Building Model From Airborne LIDAR Data Through 2-D Snake Algorithm

The snake algorithm has been proposed to solve many remote sensing and computer vision problems such as object segmentation, surface reconstruction, and object tracking. This paper introduces a framework for 3-D building model construction from LIDAR data based on the snake algorithm. It consists of nonterrain object identification, building and tree separation, building topology extraction, [...]

Contributions to Automatic Target Recognition Systems for Underwater Mine Classification

This paper deals with several original contributions to an automatic target recognition (ATR) system, which is applied to underwater mine classification. The contributions concentrate on feature selection and object classification. First, a sophisticated filter method is designed for the feature selection. This filter method utilizes a novel feature relevance measure, the composite relevance measure (CRM). [...]

Weighted Guided Image Filtering

It is known that local filtering-based edge preserving smoothing techniques suffer from halo artifacts. In this paper, a weighted guided image filter (WGIF) is introduced by incorporating an edge-aware weighting into an existing guided image filter (GIF) to address the problem. The WGIF inherits advantages of both global and local smoothing filters in the sense [...]

Compressed-Domain Ship Detection on Spaceborne Optical Image Using Deep Neural Network and Extreme Learning Machine

Ship detection on spaceborne images has attracted great interest in the applications of maritime security and traffic control. Optical images stand out from other remote sensing images in object detection due to their higher resolution and more visualized contents. However, most of the popular techniques for ship detection from optical spaceborne images have two shortcomings: [...]

On Local Prediction Based Reversible Watermarking

    This paper investigates the use of local prediction in difference expansion reversible watermarking. For each pixel, a least square predictor is computed on a square block centered on the pixel and the corresponding prediction error is expanded. The same predictor is recovered at detection without any additional information. The proposed local prediction is [...]

Combining Left and Right Palmprint Images for More Accurate Personal Identification

Multibiometrics can provide higher identification accuracy than single biometrics, so it is more suitable for some real-world personal identification applications that need high-standard security. Among various biometrics technologies, palmprint identification has received much attention because of its good performance. Combining the left and right palmprint images to perform multibiometrics is easy to implement and can [...]

Seam Searching-Based Pixel Fusion for Image Retargeting

This paper presents a new image retargeting method based on seam searching and pixel fusion. First, the importance map of the original image, which is represented by the saliency of every pixel, is generated. Second, all the pixels in the original image are divided into W (width of the original image) groups with the help [...]

A Probabilistic Approach for Color Correction in Image Mosaicking Applications

Single channel color segmentation of the Source (a) and Target (e) images. Single channel histograms, Gaussian components (dashed) and total Gaussian mass (solid black) of the source (b) and target (f ) images. 3D color segmentation of the source (c) and target (g) images. Color distribution of all pixels (green dots) and 3D Gaussian components [...]

Towards Large-Scale Histopathological Image Analysis: Hashing-Based Image Retrieval

Automatic analysis of histopathological images has been widely utilized leveraging computational image-processing methods and modern machine learning techniques. Both computer-aided diagnosis (CAD) and content-based image-retrieval (CBIR) systems have been successfully developed for diagnosis, disease detection, and decision support in this area. Recently, with the ever-increasing amount of annotated medical data, large-scale and data-driven methods have [...]

Sparse Dissimilarity-constrained Coding for Glaucoma Screening

Objective: Glaucoma is an irreversible chronic eye disease that leads to vision loss. As it can be slowed down through treatment, detecting the disease in time is important. However, many patients are unaware of the disease because it progresses slowly without easily noticeable symptoms. Currently, there is no effective method for low-cost population-based glaucoma detection [...]