Showing papers in "Journal of Visual Communication and Image Representation in 2015"

TL;DR: A Red Channel method is proposed, where colors associated to short wavelengths are recovered, as expected for underwater images, leading to a recovery of the lost contrast, and achieves a natural color correction and superior or equivalent visibility improvement when compared to other state-of-the-art methods.

TL;DR: A novel method of evaluating the complexity of image blocks, which considers multiple neighboring pixels according to the locations of different pixels, which can increase the correctness of data extraction/image recovery and reduce average extracted-bit error rate when the block size is appropriate.

TL;DR: This work presents a new approach toward copy-move forgery detection based on multi-scale analysis and voting processes of a digital image and compares the proposed method to 15 others from the literature and reports promising results.

TL;DR: This study presents a detailed overview of the CBIR framework and improvements achieved; including image preprocessing, feature extraction and indexing, system learning, benchmarking datasets, similarity matching, relevance feedback, performance evaluation, and visualization.

TL;DR: This scheme has better decrypted image quality and higher image recovery accuracy, and an adaptive evaluation function of smoothness characteristic along the isophote direction.

TL;DR: A general framework of human pose estimation is presented, and the latest technical progress on each stage is discussed, to discuss the limitations of the existing approaches and foresee the future directions to be explored.

TL;DR: The proposed reversible data hiding method with contrast enhancement can achieve more contrast enhancement effects and better visual quality for medical images and the visibility of ROI can be improved.

TL;DR: A new ghost-free multi-exposure fusion method based on dense SIFT is proposed, and two popular weight distribution strategies for local contrast extraction, namely, "weighted-average" and "winner-take-all" are studied.

TL;DR: A robust watermarking scheme in the encrypted domain is proposed, which protects the original images from the third party embedders and the hybrid discrete wavelet transform and discrete cosine transform based method improves the robust performance of theencrypted domain water marking scheme.

TL;DR: Experimental results show that the proposed method for the detection and tracking of multiple moving objects from a video sequence captured by a moving camera without additional sensors has good performance and outperforms the-state-of-art methods.

TL;DR: A local texture feature descriptor is proposed using local pattern and GLCM to extract the frequency information of local pattern map and is compared to typical state-of-the-art local patterns.

TL;DR: A high-definition video quality assessment (VQA) database that captures two typical video distortion types in video services (namely, "Compression" and "compression followed by scaling") is presented in this work.

TL;DR: One of the novel parts of the proposed gesture recognition approach is that it gives users the freedom to create gesture commands according to their preferences for selected tasks, which makes the HCI process more intuitive and user specific.

TL;DR: This paper presents a novel and unique concept of adaptive dual threshold for the detection of random valued impulse noise along with simple median filter at noise removal stage and proposes threshold computation based on averaging of pixel values of window which enhances the PSNR of the system as compared to existing median filter based image de-noising methods.

TL;DR: Extensive experimental results show that the proposed scheme outperforms five peer schemes and its two variant systems and is capable of identifying intentional tampering, incidental modification, and localizing tampered regions under mild to severe content-preserving modifications.

TL;DR: An efficient forgery detection algorithm for object removal by exemplar-based inpainting is presented, which integrates central pixel mapping (CPM), greatest zero-connectivity component labeling (GZCL) and fragment splicing detection (FSD).

TL;DR: A new reversible data hiding method based on histogram shifting using localization that has a higher embedding capacity with lower distortion and can directly find the peak point from the histogram to extract the secret data.

TL;DR: The backward-propagation neural network technique and just-noticeable difference model are incorporated into a block-wise discrete cosine transform (DCT)-based scheme to achieve effective blind image watermarking and apparently exhibits superior robustness and imperceptibility under the same payload capacity.

TL;DR: The experimental results show that the approach outperforms existing skeleton-based algorithms in terms of its classification accuracy and is more robust in the presence of noise when compared to the dynamic time warping algorithm for human action recognition.

TL;DR: The histogram of orientated Gabor magnitude is proposed for the extraction of image features and a noise detector is developed to reduce the probability of false matches in an efficient and robust detection algorithm for image copy move forgery.

TL;DR: A new high-fidelity reversible data hiding scheme that can introduce less image distortion at the same embedding payload is proposed using the prediction-error histogram modification technique.

TL;DR: A no-reference objective blur metric based on edge model (EMBM) is presented to address the image blur assessment problem and advocate using only the salient edge pixels to simulate the blur assessment in Human Visual System (HVS).

TL;DR: Comparing the proposed CFDM approach on CR-UESTC and SBU interaction databases, and comparing the result of CFDM with the CM and the BoW approach indicates that the recognition accuracy of three approaches is: CFDMCMBoW.

TL;DR: In this article, a simple blur-kernel estimation method is developed for blind motion deblurring, which is regularized by the newly proposed bi-l0-l2-norm regularization.

TL;DR: This paper focuses on the design of an adaptive sampling mechanism for the BCS through a deep analysis of the statistical information of each image block, and presents experimental results to show that the proposed adaptive method offers a remarkable quality improvement compared with the traditional BCS schemes.

TL;DR: A new approach for watermark extraction using support vector machine (SVM) with principal component analysis (PCA) based feature reduction with remarkable improvement in terms of robustness and security of the watermark.

TL;DR: A novel image descriptor, called Global Correlation Descriptor (GCD), is proposed to extract color and texture feature respectively so that these features have the same effect in CBIR and experimental results demonstrate that GCD is more robust and discriminative than other image descriptors in CBIr.

TL;DR: Experimental results demonstrate that the proposed approaches present a solid power of texture classification under illumination and rotation variations, significant viewpoint changes, and significant large-scale challenging conditions.

TL;DR: Experimental results show that the proposed anisotropic total variation based model for image deblurring is robust to noise and different blur kernels, but also performs well on blurring images with more detailed textures, and the stair-casing effect is well suppressed.

TL;DR: The methods of row-major and column-major are used to diffuse the original image and the cat map with parameter is used to scramble the image pixels, respectively, to achieve the effect of encryption.