Zhou, Yuan Rangarajan, Anand Gader, Paul D
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Hyperspectral unmixing while considering endmember variability is usually performed by the normal compositional model, where the endmembers for each pixel are assumed to be sampled from unimodal Gaussian distributions. However, in real applications, the distribution of a material is often not Gaussian. In this paper, we use Gaussian mixture models ...
Gul, M Shahzeb Khan Gunturk, Bahadir K
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture li...
Zhang, Yigong Su, Yingna Yang, Jian Ponce, Jean Kong, Hui
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a vanishing-point constrained Dijkstra road model for road detection in a stereo-vision paradigm. First, the stereo-camera is used to generate the u- and v-disparity maps of road image, from which the horizon can be extracted. With the horizon and ground region constraints, we can robustly locate the vanishing point of roa...
Ghadiyaram, Deepti Pan, Janice Bovik, Alan C
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Over-the-top adaptive video streaming services are frequently impacted by fluctuating network conditions that can lead to rebuffering events (stalling events) and sudden bitrate changes. These events visually impact video consumers' quality of experience (QoE) and can lead to consumer churn. The development of models that can accurately predict vie...
Gao, Bin Li, Xiaoqing Woo, Wai Lok Tian, Gui Yun
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Thermographic inspection has been widely applied to non-destructive testing and evaluation with the capabilities of rapid, contactless, and large surface area detection. Image segmentation is considered essential for identifying and sizing defects. To attain a high-level performance, specific physics-based models that describe defects generation an...
Green, Oded
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Median filtering is a smoothing technique for noise removal in images. While there are various implementations of median filtering for a single-core CPU, there are few implementations for accelerators and multi-core systems. Many parallel implementations of median filtering use a sorting algorithm for rearranging the values within a filtering windo...
Duan, Ling-Yu Sun, Wei Zhang, Xinfeng Wang, Shiqi Chen, Jie Yin, Jianxiong See, Simon Huang, Tiejun Kot, Alex C Gao, Wen
...
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The compact descriptors for visual search (CDVS) standard from ISO/IEC moving pictures experts group has succeeded in enabling the interoperability for efficient and effective image retrieval by standardizing the bitstream syntax of compact feature descriptors. However, the intensive computation of a CDVS encoder unfortunately hinders its widely de...
Zhang, He Patel, Vishal M
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
We propose novel convolutional sparse and low-rank coding-based methods for cartoon and texture decomposition. In our method, we first learn a set of generic filters that can efficiently represent cartoon-and texture-type images. Then, using these learned filters, we propose two optimization frameworks to decompose a given image into cartoon and te...
Zeng, Jiajian Liu, Siyuan Li, Xi Mahdi, Debbah Abderrahmane Wu, Fei Wang, Gang
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Facial landmark detection is typically cast as a point-wise regression problem that focuses on how to build an effective image-to-point mapping function. In this paper, we propose an end-to-end deep learning approach for contextually discriminative feature construction together with effective facial structure modeling. The proposed learning approac...
He, Li Zhang, Hong
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
A fundamental problem in Nyström-based kernel matrix approximation is the sampling method by which training set is built. In this paper, we suggest to use kernel -means sampling, which is shown in our works to minimize the upper bound of a matrix approximation error. We first propose a unified kernel matrix approximation framework, which is able to...
