Fast Thermal Infrared Image Restoration Method Based on On-Orbit Invariant Modulation Transfer Function

光传递函数 计算机科学 遥感 计算机视觉 人工智能 传递函数 图像复原 光学 地质学 图像处理 物理 图像(数学) 电气工程 工程类
作者
Lintong Qi,Rongguo Zhang,Zhuoyue Hu,Liyuan Li,Qiyao Wang,Xinyue Ni,Fansheng Chen
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing [Institute of Electrical and Electronics Engineers]
卷期号:62: 1-15 被引量:4
标识
DOI:10.1109/tgrs.2024.3350244
摘要

Altough the thermal infrared remote sensing camera plays a pivotal role in Earth observation, and impact the target detection, surface temperature inversion, and subsequent space missionss ignificantly,the imaging quality of the camera is constrained by its optics, image sensors, and electronics during on-orbit operation. At the same time, the traditional blind recovery algorithms, which requires extensive time for estimating intricate blur kernels, encounter challenges due to varying atmospheric conditions and other factors leading to dissimilar blur kernels across different observation scenes. In this context, this paper introduces a rapid image recovery algorithm rooted in the concept of the invariant modulation transfer function (IMTF) specific to on-orbit cameras. The IMTF model remains stable and impervious to influences stemming from ground targets, atmospheric conditions, and orbital or environmental fluctuations, contingent upon the camera’s inherent characteristics. The extraction of the IMTF involves subjecting the transfer function’s region to a modified edge methodology, followed by image recovery through a hyper-Laplacian prior inverse convolution approach. The resolution of the inverse problem is achieved by employing an alternating minimisation scheme. This method addresses the mitigation of imaging artifacts originating from the camera’s limitations.Comparative analysis against state-of-the-art image recovery techniques establishes the competitiveness of the method proposed in this paper, both in terms of recovery efficacy and operational efficiency. Substantiating this, experimental validation using in-orbit thermal infrared remote sensing images reveals a notable improvement in the average gradient (by a factor of 3.2), edge intensity (by a factor of 2.5), and modulation transfer function (by a factor of 1.3) of the restored images. Consequently, this approach introduces a novel perspective for enhancing the restoration of in-orbit remote sensing images.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
所所应助蓝天采纳,获得30
1秒前
知性的绫完成签到,获得积分10
1秒前
GG完成签到 ,获得积分10
2秒前
草莓燕麦大酸奶完成签到,获得积分10
3秒前
colammu关注了科研通微信公众号
4秒前
Elytra完成签到,获得积分10
5秒前
上官若男应助huanhuan采纳,获得10
6秒前
羽言完成签到,获得积分10
7秒前
qianyu完成签到,获得积分10
8秒前
8秒前
lkgxwpf发布了新的文献求助10
10秒前
Hexagram完成签到 ,获得积分10
11秒前
科研通AI6.4应助uraylong采纳,获得10
11秒前
xiaoyang111完成签到,获得积分10
11秒前
Nana发布了新的文献求助10
11秒前
昏睡的帆布鞋完成签到 ,获得积分10
12秒前
13秒前
简单山水完成签到,获得积分10
14秒前
霸气的思柔完成签到,获得积分10
16秒前
16秒前
lzd发布了新的文献求助10
17秒前
17秒前
usdeoo发布了新的文献求助10
22秒前
GGGrigor完成签到,获得积分0
22秒前
vv完成签到,获得积分10
22秒前
22秒前
金jin完成签到,获得积分10
24秒前
huanhuan发布了新的文献求助10
27秒前
29秒前
今后应助Zhenggg采纳,获得10
30秒前
colammu发布了新的文献求助30
32秒前
tugg188完成签到,获得积分10
32秒前
顺利的夜梦完成签到,获得积分10
33秒前
MR完成签到 ,获得积分10
33秒前
蓝天发布了新的文献求助30
33秒前
科研通AI6.3应助uraylong采纳,获得10
35秒前
37秒前
iNk应助予秋采纳,获得10
38秒前
39秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359581
求助须知:如何正确求助?哪些是违规求助? 8173554
关于积分的说明 17214712
捐赠科研通 5414579
什么是DOI,文献DOI怎么找? 2865562
邀请新用户注册赠送积分活动 1842883
关于科研通互助平台的介绍 1691105