Texture represents spatial or statistical repetition in pixel intensity and orientation. Brain tumor is an abnormal cell or tissue forms within a brain. In this paper, a model based on texture feature is useful to detect the MRI brain tumor images. There are two parts, namely; feature extraction process and classification. First, the texture features are extracted using techniques like Curvelet...

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information's relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Marko...

Advance medical imaging requires storage of large quantities of digitized clinical data. Due to the bandwidth and storage limitations, medical images must be compressed before transmission and storage. Diagnosis is effective only when compression techniques preserve all the relevant and important image information needed. There are basically two types of image compression: lossless and lossy. L...

The dyadic wavelet has good multi-scale edge detection and sub-band correlation features. Contourlet transformation has multi-directional characteristics. So a new dyadic nonsampling contourlet transformation is constructed. Firstly, multi-scale decomposition is performed on source images using dyadic contourlet transform to get high-frequency and low-frequency images. And then, according to th...

Combined with image processes under microbeam analysis,and based on analyzing the feature of electron probe deeply,the paper presents an optimized method based on Contourlet-lifting wavelet transform and regional variance.firstly,to get the fused image before Contourlet fusion based on regional variance,and then the processing image and the target image will be fused under lifting wavelet trans...

Palmprint recognition is an accepted and widely used biometric. Richness of feature and the less cost involved in acquisition make it more reliable and user friendly. The region of interest is extracted from the palmprint image as a preprocessing step. Contourlet transform, a pyramidal directional filter bank is then applied to capture both local and global details of the palmprint. The large n...

In this paper, a new multi-resolution tool, namely contourlet transform, is used to extract features for face recognition, which efficiently exploits the local spatial variations in a face image. Multi-resolution ideas, notably the wavelet transform, have been profusely employed for addressing the problem of face recognition. However, theoretical studies indicate that digital contourlet transfo...

In the contourlet transform (CT), the Laplacian pyramid (LP) decomposes an image into a low-frequency (LF) subband and a high-frequency (HF) subband. The LF subband is created by filtering the original image with 2-D low-pass filter. However, the HF subband is created by subtracting the synthesized LF subband from the original image but not by 2-D high-pass filtering the original image. In this...

The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known.A ―true‖ two dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. The main challenge in exploring geometry in images comes from the discrete nature of the ...