71 citations · 170 across the 38 of their papers we have counts for
15 papers · 1 filter
Alignment of Similarity-Transformed Images Based on Fourier--Mellin Transform Using Auxiliary Function Method
Shinji Yamashita, Yuma Kinoshita, Hitoshi Kiya
This paper proposes an algorithm for estimating the similarity transformation, namely translation, scale, and rotation, between two images with subpixel accuracy. Image registratio…
Boundary-Continuous Cross-Camera RGB Mapping via Hue-Split Model Trees
Yuma Kinoshita, Hitoshi Kiya
We propose a hue-split model-tree method for boundary-continuous cross-camera RGB mapping. Cross-camera RGB mapping aims to produce consistent color representations across cameras…
Separated-Spectral-Distribution Estimation Based on Bayesian Inference with Single RGB Camera
Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a novel method for separately estimating spectral distributions from images captured by a typical RGB camera. The proposed method allows us to separately…
Deep Retinex Network for Estimating Illumination Colors with Self-Supervised Learning
Kouki Seo, Yuma Kinoshita, Hitoshi Kiya
We propose a novel Retinex image-decomposition network that can be trained in a self-supervised manner. The Retinex image-decomposition aims to decompose an image into illumination…
Checkerboard-Artifact-Free Image-Enhancement Network Considering Local and Global Features
Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a novel convolutional neural network (CNN) that never causes checkerboard artifacts, for image enhancement. In research fields of image-to-image translati…
Image Transformation Network for Privacy-Preserving Deep Neural Networks and Its Security Evaluation
Hiroki Ito, Yuma Kinoshita, Hitoshi Kiya
We propose a transformation network for generating visually-protected images for privacy-preserving DNNs. The proposed transformation network is trained by using a plain image data…
Hue-Correction Scheme Considering Non-Linear Camera Response for Multi-Exposure Image Fusion
Kouki Seo, Chihiro Go, Yuma Kinoshita +1
We propose a novel hue-correction scheme for multi-exposure image fusion (MEF). Various MEF methods have so far been studied to generate higher-quality images. However, there are f…
Hue Correction Scheme for Multi-Exposure Image Fusion Considering Hue Distortion in Input Images
Kouki Seo, Chihiro Go, Yuma Kinoshita +1
We propose a novel hue-correction scheme for multi-exposure image fusion (MEF). Various MEF methods have so far been studied to generate higher-quality images. However, there are f…
Fixed smooth convolutional layer for avoiding checkerboard artifacts in CNNs
Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a fixed convolutional layer with an order of smoothness not only for avoiding checkerboard artifacts in convolutional neural networks (CNNs) but also for…
An Image Fusion Scheme for Single-Shot High Dynamic Range Imaging with Spatially Varying Exposures
Chihiro Go, Yuma Kinoshita, Sayaka Shiota +1
This paper proposes a novel multi-exposure image fusion (MEF) scheme for single-shot high dynamic range imaging with spatially varying exposures (SVE). Single-shot imaging with SVE…
A hue-preserving tone mapping scheme based on constant-hue plane without gamut problem
Yuma Kinoshita, Kouki Seo, Artit Visavakitcharoen +1
We propose a novel hue-preserving tone mapping scheme. Various tone mapping operations have been studied so far, but there are very few works on color distortion caused in image to…
Single-Shot High Dynamic Range Imaging with Spatially Varying Exposures Considering Hue Distortion
Chihiro Go, Yuma Kinoshita, Sayaka Shiota +1
We proposes a novel single-shot high dynamic range imaging scheme with spatially varying exposures (SVE) considering hue distortion. Single-shot imaging with SVE enables us to capt…
A Color Compensation Method Using Inverse Camera Response Function for Multi-exposure Image Fusion
Artit Visavakitcharoen, Yuma Kinoshita, Hitoshi Kiya
Multi-exposure image fusion is a method for producing an image with a wide dynamic range by fusing multiple images taken under various exposure values. In this paper, we discuss co…
Convolutional Neural Networks Considering Local and Global features for Image Enhancement
Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a novel convolutional neural network (CNN) architecture considering both local and global features for image enhancement. Most conventional image enhancem…
Deep Inverse Tone Mapping Using LDR Based Learning for Estimating HDR Images with Absolute Luminance
Yuma Kinoshita, Hitoshi Kiya
In this paper, a novel inverse tone mapping method using a convolutional neural network (CNN) with LDR based learning is proposed. In conventional inverse tone mapping with CNNs, g…