Unsupervised Deep Noise Modeling for Hyperspectral Image Change Detection
نویسندگان
چکیده
منابع مشابه
Rough Clustering Based Unsupervised Image Change Detection
This paper introduces an unsupervised technique to detect the changed region of multitemporal images on a same reference plane with the help of rough clustering. The proposed technique is a soft-computing approach, based on the concept of rough set with rough clustering and Pawlak’s accuracy. It is less noisy and avoids pre-deterministic knowledge about the distribution of the changed and uncha...
متن کاملDeep Unsupervised Domain Adaptation for Image Classification via Low Rank Representation Learning
Domain adaptation is a powerful technique given a wide amount of labeled data from similar attributes in different domains. In real-world applications, there is a huge number of data but almost more of them are unlabeled. It is effective in image classification where it is expensive and time-consuming to obtain adequate label data. We propose a novel method named DALRRL, which consists of deep ...
متن کاملAutomatic analysis of the difference image for unsupervised change detection
One of the main problems related to unsupervised change detection methods based on the “difference image” lies in the lack of efficient automatic techniques for discriminating between changed and unchanged pixels in the difference image. Such discrimination is usually performed by using empirical strategies or manual trial-and-error procedures, which affect both the accuracy and the reliability...
متن کاملUnsupervised hyperspectral image analysis with projection pursuit
Principal components analysis (PCA) is effective at compressing information in multivariate data sets by computing orthogonal projections that maximize the amount of data variance. Unfortunately, information content in hyperspectral images does not always coincide with such projections. We propose an application of projection pursuit (PP), which seeks to find a set of projections that are “inte...
متن کاملUnsupervised Image Segmentation based on Texems for Hyperspectral data
There is no doubt about how useful and valuable the information provided by the hyperspectral sensors can be. Image segmentation procedures can take advantage of this information to increase the ability for separating different textures in an image. A multiscale approach for segmenting hyperspectral images is presented in this work. The method is based on the recently proposed texem model which...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Remote Sensing
سال: 2019
ISSN: 2072-4292
DOI: 10.3390/rs11030258