Gradient Domain Weighted Guided Image Filtering
원문 초록
Guided image filter is a well-known local filter in image processing. However, the presence of halo artifacts is a common issue associated with this type of filter. This paper proposes an algorithm that utilizes gradient information to accurately identify the edges of an image. Furthermore, the algorithm uses weighted information to distinguish flat areas from edge areas, resulting in sharper edges and reduced blur in flat areas. This approach mitigates the excessive blurring near edges that often leads to halo artifacts. Experimental results demonstrate that the proposed algorithm significantly suppresses halo artifacts at the edges, making it highly effective for both image denoising and detail enhancement.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Energy-Based Transformers are Scalable Learners and Thinkers
STAR-Net: An Interpretable Model-Aided Network for Remote Sensing Image Denoising
Optimal Density Functions for Weighted Convolution in Learning Models
Optimal Weighted Convolution for Classification and Denosing
Rotation-Equivariant Self-Supervised Method in Image Denoising
Degradation-Aware Feature Perturbation for All-in-One Image Restoration
토론
이 논문과 연결된 포럼 글이 아직 없습니다.