Results 21 to 30 of about 15,597 (201)

Exact Histogram Specification Optimized for Structural Similarity

, 2008
An exact histogram specification (EHS) method modifies its input image to have a specified histogram. Applications of EHS include image (contrast) enhancement (e.g., by histogram equalization) and histogram watermarking.
Alireza Nasiri Avanaki, D. Coltuc, D. Coltuc, D. Coltuc, D. Coltuc, E. L. Hall, H. Zhu, I.-L. Jung, J. A. Stark, J. Y. Kim, M. Barni, P. J. S. G. Ferreira, R. C. Gonzales, R. C. Gonzales, S.-C. Pei, T. H. Cormen, V. Caselles, Y. J. Zhang, Y. Wan, Z. Wang, Z. Wang   +20 more
core   +1 more source

Classification of synoptic circulation patterns with a two-stage clustering algorithm using the modified structural similarity index metric (SSIM) [PDF]

Earth System Dynamics
We develop a new classification method for synoptic circulation patterns with the aim to extend the evaluation routine for climate simulations. This classification is applicable to any region of the globe of any size given the reference data.
K. Winderlich, C. Dalelane, A. Walter
doaj   +1 more source

Multi-threshold Segmentation Method with High Accuracy and Adaptability Using Circular Histogram Linearization [PDF]

Jisuanji gongcheng
To address the problems of low segmentation accuracy and poor adaptability of existing multi-threshold segmentation methods for color images, a multi-threshold segmentation method with high accuracy and adaptability based on circular histogram ...
Cong HUANG, Yaobin ZOU, Shuifa SUN
doaj   +1 more source

Full Reference Objective Quality Assessment for Reconstructed Background Images

, 2018
With an increased interest in applications that require a clean background image, such as video surveillance, object tracking, street view imaging and location-based services on web-based maps, multiple algorithms have been developed to reconstruct a ...
Karam, Lina, Shrotre, Aditee
core   +1 more source

Learning to Generate Images with Perceptual Similarity Metrics

, 2017
Deep networks are increasingly being applied to problems involving image synthesis, e.g., generating images from textual descriptions and reconstructing an input image from a compact representation.
Liao, Renjie, Mozer, Michael C., Ridgeway, Karl, Roads, Brett D., Snell, Jake, Zemel, Richard S.   +5 more
core   +1 more source

Sparse Representation-based Image Quality Assessment

, 2013
A successful approach to image quality assessment involves comparing the structural information between a distorted and its reference image. However, extracting structural information that is perceptually important to our visual system is a challenging ...
Guha, Tanaya, Nezhadarya, Ehsan, Ward, Rabab K   +2 more
core   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

In Situ Characterisation of Hydrogels via Dynamic Interface Printing

Advanced Science, EarlyView.
ABSTRACT Hydrogels have become pivotal materials for tissue engineering, robotics, biomedical devices, and sensing applications due to their diverse material compositions and tunable mechanical properties. While significant effort has focused on developing novel manufacturing approaches such as extrusion bioprinting and light‐based fabrication methods,
Callum Vidler, Michael Halwes, David J. Collins   +2 more
wiley   +1 more source

Deep Multiple Description Coding by Learning Scalar Quantization

, 2019
In this paper, we propose a deep multiple description coding framework, whose quantizers are adaptively learned via the minimization of multiple description compressive loss. Firstly, our framework is built upon auto-encoder networks, which have multiple
Bai, Huihui, Wang, Anhong, Zhao, Lijun, Zhao, Yao   +3 more
core   +1 more source

Deep Learning‐Powered Scalable Cancer Organ Chip for Cancer Precision Medicine

Advanced Science, EarlyView.
This scalable, low‐cost Organ Chip platform, made via injection molding, uses capillary pinning for hydrogel confinement and supports versatile tissue coculture and robust imaging. Deep learning enables label‐free, sensitive phenotypic analysis.
Yu‐Chieh Yuan, Beibei Xu, Jenna McCormack, XuHai Huang, Jingzhe Ma, Thomas Marshall, Yacong Sun, Hardeep Singh, Alyssa Fanelli, Gauri Kulkarni, Ji Hye Seo, Paige Gilbride, Bing Wei, Bo Wang, Yanyan Liu, Fei Ma, Lin Zhou, Shuyang Wang, Xiaohua Qian, Zhiyong Xie, Polina Golland, Longlong Si, Yu Shrike Zhang, Xin Xie, Haiqing Bai   +24 more
wiley   +1 more source