Sinusoidal signal models are a useful representation of local image structure, as sinusoid phase describes symmetry separately from strength and orientation. Existing models consist of one or two oriented sinusoids, calculated using the 0th to 3rd order Riesz transforms. We propose an expanded signal model consisting of a larger number of oriented sinusoids. The model parameters are estimated using higher-order Riesz transforms and a novel application of super-resolution theory. Image features consisting of multiple lines or edges can be analysed using the method, which compares favourably to existing approaches
This paper will give an overview of the sinusoidal model, its properties, and variations made upon i...
Two new methods are presented for the estimation of the frequencies of closely spaced complex valued...
The monogenic signal is the natural 2-D counterpart of the 1-D analytic signal. We propose to transp...
Sinusoidal signal models are a useful representation of local image structure, as sinusoid phase des...
The monogenic signal consists of an image and its first-order Riesz transform. It describes signal s...
Rich descriptions of local image structures are important for higher-level understanding of images i...
We introduce a sinusoidal image model consisting of an oriented sinusoid plus a residual component. ...
The 2D-complex Riesz transform is an extension of the Hilbert transform to images. It can be used to...
A useful technique is presented to compactly represent multidimensional signals employing two or mor...
AbstractTo represent the local orientation and energy of a 1-D image signal, many models of early vi...
AbstractWe introduce a new local sine transform that can completely localize image information both ...
<p> For applications such as remote sensing imaging and medical imaging, high-resolution (HR) image...
Abstract. This work introduces a novel method to estimate the char-acteristic scale of low-level ima...
More information is presented about improved methods for estimation of the frequencies of sinusoids ...
Super-resolution considers the problem of increasing the spatial resolution of an image or video fro...
This paper will give an overview of the sinusoidal model, its properties, and variations made upon i...
Two new methods are presented for the estimation of the frequencies of closely spaced complex valued...
The monogenic signal is the natural 2-D counterpart of the 1-D analytic signal. We propose to transp...
Sinusoidal signal models are a useful representation of local image structure, as sinusoid phase des...
The monogenic signal consists of an image and its first-order Riesz transform. It describes signal s...
Rich descriptions of local image structures are important for higher-level understanding of images i...
We introduce a sinusoidal image model consisting of an oriented sinusoid plus a residual component. ...
The 2D-complex Riesz transform is an extension of the Hilbert transform to images. It can be used to...
A useful technique is presented to compactly represent multidimensional signals employing two or mor...
AbstractTo represent the local orientation and energy of a 1-D image signal, many models of early vi...
AbstractWe introduce a new local sine transform that can completely localize image information both ...
<p> For applications such as remote sensing imaging and medical imaging, high-resolution (HR) image...
Abstract. This work introduces a novel method to estimate the char-acteristic scale of low-level ima...
More information is presented about improved methods for estimation of the frequencies of sinusoids ...
Super-resolution considers the problem of increasing the spatial resolution of an image or video fro...
This paper will give an overview of the sinusoidal model, its properties, and variations made upon i...
Two new methods are presented for the estimation of the frequencies of closely spaced complex valued...
The monogenic signal is the natural 2-D counterpart of the 1-D analytic signal. We propose to transp...