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A feature extraction method based on two-dimensional (2D) mel-cepstrum is introduced. The concept of one-dimensional (1D) mel-cepstrum which is widely used in speech recognition is extended to 2D in this article. Feature matrices resulting from the 2D mel-cepstrum, Fourier LDA, 2D PCA and original image matrices are converted to feature vectors and(More)
In this article, an image feature extraction method based on two-dimensional (2D) Mellin cepstrum is introduced. The concept of one-dimensional (1D) mel-cepstrum that is widely used in speech recognition is extended to two-dimensions using both the ordinary 2D Fourier transform and the Mellin transform. The resultant feature matrices are applied to two(More)
Features extracted at salient points are used to construct a region covariance descriptor (RCD) for target tracking. In the classical approach, the RCD is computed by using the features at each pixel location, which increases the computational cost in many cases. This approach is redundant because image statistics do not change significantly between(More)
Image fusion is an image processing technique that is applied in various application areas. Image fusion is adopted for target detection and recognition in surveillance systems, recognition and diagnosis for medical imaging systems and for surface characteristics determination on multi-spectral satellite images. Structure of the techniques and the content(More)
Compressive sensing framework states that a signal which has sparse representation in a known basis may be reconstructed from samples obtained from a sub-Nyquist sampling rate. Due to its inherent properties, the Fourier domain is widely used in compressive sensing applications. Sparse signal recovery applications making use of a small number of Fourier(More)
In this work, the application of compressive sensing theory to single detector seekers is investigated. Compressive sensing is a novel signal processing technique which shows that a compressible signal can be constructed using fewer measurements obtained in a specific way below the Nyquist rate. Single detector image reconstruction applications using(More)
In this study, a feature based tracker is developed in order to track platforms above sea-level in visual band videos. The covariance descriptor, known as an efficient method in object detection and classification problems, is used in the feature extraction phase of the tracker. The features or feature sets, extracted from the images in the database that is(More)