[PDF] Top 20 Hyperspectral image classification with SVM and guided filter

... the classification accuracy for each class, OA, AA, and KA is adopted to evaluate the classification ...the classification maps obtained by dif- ferent methods associated with the corresponding OA ... See full document

... tral image classification. Hyperspectral image classification accuracy depends on the number of classes, training samples and features space ...The classification performance ... See full document

... preserving Guided filter performs very well in terms of both quality and efficiency in a great variety of applications, such as noise reduction, detail smoothing/enhancement, HDR compression, image ... See full document

... based classification techniques which transforms the data into new domain to extract potentially better features (Villa et ...for classification of HSI is a challenge due to its high spectral data (Samat et ... See full document

... supervised hyperspectral classification is to group pixels into different classes with the classifiers trained by the given training sam- ...HSI classification methods have been proposed, based on ... See full document

... image classification. In the preprocessing step, we adopted a mean filter and a Gaussian filter as examples of smoothing and denoising ...The SVM was implemented using the LIBSVM ... See full document

... for hyperspectral image classification, ...the hyperspectral image ...and classification ac- ...of classification accuracy, while in terms of computational time it is ... See full document

... the image. Here comes the advantage of using hyperspectral imaging and feature extraction ...method. Hyperspectral images are taken using ...based classification method is applied to the ... See full document

... quiet image. The Wiener filter may additionally be used for ...This filter is that the mean squares error-optimal stationary linear filter for pictures degraded by additive noise and ...Wiener ... See full document

... the SVM and FODPSO- FCM are incorporated through a majority voting process, from which the final classification map is formed using ...of SVM which can handle high-dimensional information with a ... See full document

... The models with shallow and deep feature representations are used to determine the utility of self-taught training method [21]. Each model is trained on multiple unlabeled HSI datasets for adding spatiospectral variation ... See full document

... Pixel-wise classification methods process each pixel independently without considering the spatial informa- tion, but spatial contextual information of HSI is as impor- tant as the spectral information ...of ... See full document

... content-based image retrieval (CBIR) system. This system enables both multi-image query and slide –level image retrieval in order to protect the semantic consistency among the retrieved ...of ... See full document

... the classification of hyperspectral images with ...the SVM is able to proficientlycategorize high-dimensional data with limited ...overall classification accuracy and kappa ... See full document

... Firstly, SVM was observed to have the worst ...high classification accuracy when using a small number of training ...Secondly, image-based classifiers ...higher classification accuracy ... See full document

... Number of algorithms were developed earlier for color based image retrieval. In this era conventional histogram based matching and dominant color region based indexing technique was the early. The main drawback of ... See full document

... use SVM as a classifier for the classification of image and apply this classification process to all the features of image which are extract from feature extraction ... See full document

... based image retrieval refers to search for an image from the huge database to retrieve an image with the required shape, text or ...Content-based image retrieval are judged on the parameters ... See full document

... tion of the HSI pixel may not have a promising edge-preserving performance. As aforementioned in the introduction (section 1), several literatures have studied the improvement of the JSM by adopting size/shape adaptive ... See full document

... Before DDID, there are several state-of-art approaches which combine both domain such as BM3D [15], shape- adaptive BM3D (SA-BM3D) [16] and BM3D with shape-adaptive principal component analysis (BM3D- SAPCA) [10]. They ... See full document