17 citations · 57 across the 24 of their papers we have counts for
6 papers · 1 filter
A Retinex-based Image Enhancement Scheme with Noise Aware Shadow-up Function
Chien Cheng Chien, Yuma Kinoshita, Sayaka Shiota +1
This paper proposes a novel image contrast enhancement method based on both a noise aware shadow-up function and Retinex (retina and cortex) decomposition. Under low light conditio…
Privacy-Preserving SVM Computing by Using Random Unitary Transformation
Takahiro Maekawa, Takayuki Nakachi, Sayaka Shiota +1
A privacy-preserving Support Vector Machine (SVM) computing scheme is proposed in this paper. Cloud computing has been spreading in many fields. However, the cloud computing has so…
A Pseudo Multi-Exposure Fusion Method Using Single Image
Yuma Kinoshita, Sayaka Shiota, Hitoshi Kiya
This paper proposes a novel pseudo multi-exposure image fusion method based on a single image. Multi-exposure image fusion is used to produce images without saturation regions, by…
Multi-Exposure Image Fusion Based on Exposure Compensation
Yuma Kinoshita, Taichi Yoshida, Sayaka Shiota +1
This paper proposes a novel multi-exposure image fusion method based on exposure compensation. Multi-exposure image fusion is a method to produce images without color saturation re…
Super-Resolution using Convolutional Neural Networks without Any Checkerboard Artifacts
Yusuke Sugawara, Sayaka Shiota, Hitoshi Kiya
It is well-known that a number of excellent super-resolution (SR) methods using convolutional neural networks (CNNs) generate checkerboard artifacts. A condition to avoid the check…
Automatic Exposure Compensation for Multi-Exposure Image Fusion
Yuma Kinoshita, Sayaka Shiota, Hitoshi Kiya
This paper proposes a novel luminance adjustment method based on automatic exposure compensation for multi-exposure image fusion. Multi-exposure image fusion is a method to produce…