Cover Image

Exploring Distortion Prior with Latent Diffusion Models for Remote Sensing Image Compression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Junhui, Li, Jutao, Hou, Xingsong, Wang, Huake
Format:	Preprint
Published:	2024
Subjects:	Image and Video Processing Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Exploiting Inter-Image Similarity Prior for Low-Bitrate Remote Sensing Image Compression
by: Li, Junhui, et al.
Published: (2024)

Enhancing Perception Quality in Remote Sensing Image Compression via Invertible Neural Network
by: Li, Junhui, et al.
Published: (2024)

Dual Degradation-Inspired Deep Unfolding Network for Low-Light Image Enhancement
by: Wang, Huake, et al.
Published: (2023)

Controllable Distortion-Perception Tradeoff Through Latent Diffusion for Neural Image Compression
by: Zhou, Chuqin, et al.
Published: (2024)

Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Prior
by: Li, Zhiyuan, et al.
Published: (2024)

UP-Diff: Latent Diffusion Model for Remote Sensing Urban Prediction
by: Wang, Zeyu, et al.
Published: (2024)

Probabilistic-based Feature Embedding of 4-D Light Fields for Compressive Imaging and Denoising
by: Lyu, Xianqiang, et al.
Published: (2023)

Latent Diffusion Prior Enhanced Deep Unfolding for Snapshot Spectral Compressive Imaging
by: Wu, Zongliang, et al.
Published: (2023)

Ultra-Low Complexity On-Orbit Compression for Remote Sensing Imagery via Block Modulated Imaging
by: Wang, Zhibin, et al.
Published: (2024)

Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing Images
by: Wu, Hanlin, et al.
Published: (2024)

Single-Step Latent Consistency Model for Remote Sensing Image Super-Resolution
by: Sun, Xiaohui, et al.
Published: (2025)

MoE-DiffIR: Task-customized Diffusion Priors for Universal Compressed Image Restoration
by: Ren, Yulin, et al.
Published: (2024)

TLIC: Learned Image Compression with ROI-Weighted Distortion and Bit Allocation
by: Jiang, Wei, et al.
Published: (2024)

RSAM-Seg: A SAM-based Approach with Prior Knowledge Integration for Remote Sensing Image Semantic Segmentation
by: Zhang, Jie, et al.
Published: (2024)

From Noise to Latent: Generating Gaussian Latents for INR-Based Image Compression
by: Lin, Chaoyi, et al.
Published: (2025)

A Diffusion-Based Framework for Terrain-Aware Remote Sensing Image Reconstruction
by: Yu, Zhenyu, et al.
Published: (2025)

Generative Latent Coding for Ultra-Low Bitrate Image Compression
by: Jia, Zhaoyang, et al.
Published: (2025)

Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing
by: Hackstein, Jakob, et al.
Published: (2024)

Enhancing Low-light Light Field Images with A Deep Compensation Unfolding Network
by: Lyu, Xianqiang, et al.
Published: (2023)

Balanced Rate-Distortion Optimization in Learned Image Compression
by: Zhang, Yichi, et al.
Published: (2025)

LDPM: Towards undersampled MRI reconstruction with MR-VAE and Latent Diffusion Prior
by: Tang, Xingjian, et al.
Published: (2024)

DLF: Extreme Image Compression with Dual-generative Latent Fusion
by: Xue, Naifu, et al.
Published: (2025)

Generative Latent Coding for Ultra-Low Bitrate Image and Video Compression
by: Qi, Linfeng, et al.
Published: (2025)

Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution
by: Sui, Jialu, et al.
Published: (2024)

Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery
by: Han, Chengxi, et al.
Published: (2024)

Prior-guided Diffusion Model for Cell Segmentation in Quantitative Phase Imaging
by: Shao, Zhuchen, et al.
Published: (2024)

Rate-Distortion-Cognition Controllable Versatile Neural Image Compression
by: Liu, Jinming, et al.
Published: (2024)

Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion
by: Ballé, Jona, et al.
Published: (2024)

DehazeMamba: SAR-guided Optical Remote Sensing Image Dehazing with Adaptive State Space Model
by: Zhao, Zhicheng, et al.
Published: (2025)

Semantic Ensemble Loss and Latent Refinement for High-Fidelity Neural Image Compression
by: Li, Daxin, et al.
Published: (2024)

Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion
by: Shen, Huanfeng, et al.
Published: (2021)

Generative Latent Video Compression
by: Guo, Zongyu, et al.
Published: (2025)

SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
by: Zhong, Yu, et al.
Published: (2024)

Controlling Rate, Distortion, and Realism: Towards a Single Comprehensive Neural Image Compression Model
by: Iwai, Shoma, et al.
Published: (2024)

HPGN: Hybrid Priors-Guided Network for Compressed Low-Light Image Enhancement
by: Li, Hantang, et al.
Published: (2025)

An Integrated Framework for the Heterogeneous Spatio-Spectral-Temporal Fusion of Remote Sensing Images
by: Jiang, Menghui, et al.
Published: (2021)

A Contrastive Learning Foundation Model Based on Perfectly Aligned Sample Pairs for Remote Sensing Images
by: Shen, Hengtong, et al.
Published: (2025)

Compact Latent Representation for Image Compression (CLRIC)
by: Ameen, Ayman A., et al.
Published: (2025)

Lossy Image Compression with Foundation Diffusion Models
by: Relic, Lucas, et al.
Published: (2024)

SG-JND: Semantic-Guided Just Noticeable Distortion Predictor For Image Compression
by: Cao, Linhan, et al.
Published: (2024)