Abstract

Satellite images have gained a wide popularity in the field of content-based image retrieval. A massive amount of these images are collected every year due to the high availability of satellites and computer technologies. However, extracting user-specific content from these images still remains a primary concern due to the presence of semantic gap. This limits the capabilities of CBIR. Therefore, an effective and efficient method is required for image retrieval. This paper puts forward a semantic-based image retrieval approach along with the advantages of hashing for better feature extraction and precise retrieval. Hashing accelerates the quality of similarity search among images by generating unique image-hash codes .This approach also aims to scale down the problems related to semantic gap for better retrieval results.

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