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The purpose of this paper is to analyze the spectrum influence between radon transform and log‐polar transform when rotation and scale effect is eliminated. The average retrieval performance of wavelet and NSCT with different retrieval parameters is also studied.

The authors designed a multi‐scale and multi‐orientation texture transform spectrum, as well as rotation‐invariant feature vector and its measurement criteria. Then a new two‐level coarse‐to‐fine rotation and scale‐invariant texture retrieval algorithm based on no‐parameter statistic features was proposed. Experiments on VisTex texture database show that the algorithm proposed in this paper is appropriate for main orientation capturing and detail information description.

According to the experiments results, it was found that the combination of this two‐level progressive retrieval strategy and multi‐scale analysis method can effectively improve retrieval efficiency compared with traditional algorithms and ensure a high precision as well.

The paper presents a novel algorithm for rotation and scale‐invariant texture retrieval.

This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images.

A novel remote sensing image retrieval method based on VSP (visual salient point) features is proposed in this paper. A key point detector and descriptor are used to extract the critical features and their descriptors in remote sensing images. A visual attention model is adopted to calculate the saliency map of the images, separating the salient regions from the background in the images. The key points in the salient regions are then extracted and defined as VSPs. The VSP features can then be constructed. The similarity between images is measured using the VSP features.

According to the experiment results, compared with traditional visual features, VSP features are more precise and stable in representing diverse remote sensing images. The proposed method performs better than the traditional methods in image retrieval precision.

This paper presents a novel remote sensing image retrieval method based on VSP features.

The purpose of this paper is to improve the retrieval results of hyperspectral image by integrating both spectral and textural features. For this purpose, an improved multiscale opponent representation for hyperspectral texture is proposed to represent the spatial information of the hyperspectral scene.

In the presented approach, end-member signatures are extracted as spectral features by means of the widely used end-member induction algorithm N-FINDR, and the improved multiscale opponent representation is extracted from the first three principal components of the hyperspectral data based on Gabor filters. Then, the combination similarity between query image and other images in the database is calculated, and the first k more similar images are returned in descending order of the combination similarity.

Some experiments are calculated using the airborne hyperspectral data of Washington DC Mall. According to the experimental results, the proposed method improves the retrieval results, especially for image categories that have regular textural structures.

The paper presents an effective retrieval method for hyperspectral images.

This paper aims to study vehicle-type strategies for the manufacturer's car sharing by accounting for consumers' behavior and the subsidy.

The authors develop a game model, in which a monopoly manufacturer that can produce gasoline vehicles (GVs) or energy vehicles (EVs) not only sells vehicles in the sales market, but also rents them out in the sharing market by the self-built platform. The manufacturer strategically chooses which type of vehicles based on consumers' behavior and whether the government provides the EVs’ subsidy.

When consumers' low-carbon awareness is relatively high or the marginal cost is low, the manufacturer chooses EVs. The manufacturer chooses GVs when the low-carbon awareness and the marginal cost are low. Only when the low-carbon awareness and the subsidy are not too low, the manufacturer who originally chose GVs launches EVs. When the low-carbon awareness is high, the excessive subsidy discourages the manufacturer from entering the sharing market. If the government provides the subsidy, the manufacturer launches high-end EVs. Otherwise, the manufacturer launches low-end EVs. Moreover, the subsidy increases consumer surplus and social welfare since the high subsidy makes EVs’ sharing market demand be negative.

This study enriches the literature on vehicle-type strategies for the manufacturer's car sharing, owns a practical significance to guide the manufacturer's operation management in the car sharing market and provides advice on whether the government should provide EVs’ subsidy.