A color image watermarking framework for copyright protection of stereo images based on binocular just noticeable difference and LU decomposition

Multimedia Tools and Applications - The copyright protection of three-dimensional (3D) content is a matter of interest in artistic and creative works due to the rights of the holder for the...     

Real-time noise suppression in 3D ultrasound imaging based on order statistics

An approach based on order statistics for speckle and impulsive noise suppression in 3D ultrasound images is presented. The proposed technique uses the rank M-type estimators and these are adapted to 3D image processing applications. The results from known techniques are compared with the proposed method to demonstrate its performance in terms of noise suppression and detail preservation. The DSP TMS320C6711 has been used to realise 3D image processing and for comparison of the processing time values.     

Parallel framework for dense disparity map estimation using Hamming distance

A novel framework for sparse and dense disparity estimation was designed, and the proposed framework has been implemented in CPU and GPU for a parallel processing capability. The Census transform is applied in the first stage, and then, the Hamming distance is later used as similarity measure in the stereo matching stage followed by a matching consistency check. Next, a disparity refinement is performed on the sparse disparity map via weighted median filtering and color K-means segmentation, in addition to clustered median filtering to obtain the dense disparity map. The results are compared with state-of-the-art frameworks, demonstrating this process to be competitive and robust. The quality criteria used are structural similarity index measure and percentage of bad pixels (B) for objective results and subjective perception via human visual system demonstrating better performance in maintaining fine features in disparity maps. The comparisons include processing times and running environments, to place each process into context.     

Parallel supervised land-cover classification system for hyperspectral and multispectral images

Hyperspectral and multispectral imagery allows remote-sensing applications such as the land-cover mapping, which is a significant baseline to understand and to monitor the Earth. Furthermore, it is a relevant process for socio-economic activities. For that reason, high land-classification accuracies are imperative, and minor image processing time is essential. In addition, the process of gathering classes’ documented samples is complicated. This implies that the classification system is required to perform with a limited number of training observations. Another point worth mentioning is that there are hardly any methods that can be used analogously for hyperspectral or multispectral images. This paper aims to propose a novel classification system that can be used for both types of images. The designed classification system is composed of a novel parallel feature extraction algorithm, which utilises a cluster of two graphics processing units in combination with a multicore central processing unit (CPU), and an artificial neural network (ANN) particularly devised for the classification of the features ensued by the implemented feature extraction method. To prove the performance of the proposed classification system, it is compared with non-parallel and CPU-only-parallel implementations employing multispectral and hyperspectral databases. Moreover, experiments with different number of samples for training the classifier are performed. Finally, the proposed ANN is compared with a state-of-the-art support vector machine in classification and processing time results.     

Acoustical multipole source in a hollow fluid-filled cylinder

The propagation of elastic waves generated by an impulse multipole source in a hollow fluid-filled cylinder was studied. The general solution of the problem is illustrated by calculations for monopole and dipole sources applied in geophysical and geoecological measurement practice. The analysis of the outer boundary influence on the waveforms registered by receivers located in the fluid was performed. The estimation has been carried out to determine a cylinder wall thickness under which its influence on cinematic parameters of the waveforms can be neglected.     

Median M-type K-nearest neighbour (MM-KNN) filter to remove impulsenoise from corrupted images

The median M-type K-nearest neighbour (MM-KNN) filter to remove impulse noise from corrupted images is presented. This filter uses R and M estimators combined with different influence functions. Simulation results have shown that the restoration performance is better than that of other known filters