71 citations · 170 across the 38 of their papers we have counts for
15 papers · 1 filter
Scale and Rotation Estimation of Similarity-Transformed Images via Cross-Correlation Maximization Based on Auxiliary Function Method
Shinji Yamashita, Yuma Kinoshita, Hitoshi Kiya
This paper introduces a highly efficient algorithm capable of jointly estimating scale and rotation between two images with sub-pixel precision. Image alignment serves as a critica…
Scene-Segmentation-Based Exposure Compensation for Tone Mapping of High Dynamic Range Scenes
Yuma Kinoshita, Hitoshi Kiya
We propose a novel scene-segmentation-based exposure compensation method for multi-exposure image fusion (MEF) based tone mapping. The aim of MEF-based tone mapping is to display h…
Template matching with white balance adjustment under multiple illuminants
Teruaki Akazawa, Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a novel template matching method with a white balancing adjustment, called N-white balancing, which was proposed for multi-illuminant scenes. To reduce th…
Image and Model Transformation with Secret Key for Vision Transformer
Hitoshi Kiya, Ryota Iijima, MaungMaung Aprilpyone +1
In this paper, we propose a combined use of transformed images and vision transformer (ViT) models transformed with a secret key. We show for the first time that models trained wit…
Privacy-Preserving Image Classification Using Vision Transformer
Zheng Qi, AprilPyone MaungMaung, Yuma Kinoshita +1
In this paper, we propose a privacy-preserving image classification method that is based on the combined use of encrypted images and the vision transformer (ViT). The proposed meth…
An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applications
Hitoshi Kiya, AprilPyone MaungMaung, Yuma Kinoshita +2
This article presents an overview of image transformation with a secret key and its applications. Image transformation with a secret key enables us not only to protect visual infor…
Self-Supervised Intrinsic Image Decomposition Network Considering Reflectance Consistency
Yuma Kinoshita, Hitoshi Kiya
We propose a novel intrinsic image decomposition network considering reflectance consistency. Intrinsic image decomposition aims to decompose an image into illumination-invariant a…
Spatially varying white balancing for mixed and non-uniform illuminants
Teruaki Akazawa, Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a novel white balance adjustment, called "spatially varying white balancing," for single, mixed, and non-uniform illuminants. By using n diagonal matrices…
Multi-color balance for color constancy
Teruaki Akazawa, Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a novel multi-color balance adjustment for color constancy. The proposed method, called "n-color balancing," allows us not only to perfectly correct n tar…
CycleGAN without checkerboard artifacts for counter-forensics of fake-image detection
Takayuki Osakabe, Miki Tanaka, Yuma Kinoshita +1
In this paper, we propose a novel CycleGAN without checkerboard artifacts for counter-forensics of fake-image detection. Recent rapid advances in image manipulation tools and deep…
Image Enhancement Network Trained by Using HDR images
Yuma Kinoshita, Hitoshi Kiya
In this paper, a novel image enhancement network is proposed, where HDR images are used for generating training data for our network. Most of conventional image enhancement methods…
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…
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…
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…