4 results about "Biorthogonal wavelet" patented technology

The present application belongs to the technical field of interferometric phase map processing, and relates to a SAR interferometric phase denoising method and device based on BM3D. A two-dimensional thread grid at a pixel level is used to realize parallel implementation of similar block position index set screening, maximum likelihood estimation of pixels and decorrelation transformation. A two-dimensional thread grid at a block level is used to realize parallel implementation of biorthogonal wavelet transformation of image blocks. A three-dimensional thread grid is used for three-dimensional block group stacking, and a two-dimensional thread grid at a block level is used to realize parallel implementation of Hadamard transformation of the third dimension of the three-dimensional block group. A three-dimensional thread grid is used for hard threshold filtering of transformation coefficients in the three-dimensional block group. A two-dimensional thread grid at a block level is used to realize parallel implementation of inverse transformation of image blocks, a first layered two-dimensional thread grid is used to realize parallel implementation of weighted aggregation of spatial domain pixels, a two-dimensional thread grid at a pixel level is used to realize parallel implementation of inverse decorrelation transformation of spatial domain pixels, and a complex interferometric image after preliminary denoising is obtained, and then secondary filtering is performed to obtain a target complex interferometric image.

The invention discloses a distributed spectrum sensing noise stripping method based on wavelet gradient, and belongs to the technical field of communication and artificial intelligence crossing. The method comprises the following steps: acquiring original spectrum data through a distributed cognitive radio node; performing sliding window segmentation, Hanning window weighting and power spectrum density calculation on the data; the preprocessed data are input into a differentiable wavelet noise separation layer, the layer serves as a learnable one-dimensional convolution kernel through a parameterized biorthogonal wavelet filter, and end-to-end trainable multi-resolution analysis is achieved in a deep learning framework; calculating the power spectrum density gradient of the high-frequency detail coefficient in real time, and quantifying the noise abrupt change intensity based on a central difference method; dynamically generating a gating weight, and selectively suppressing the wavelet coefficient of the high-gradient frequency point; inputting the processed data into a one-dimensional convolutional neural network with residual connection for classification; and results are fused by adopting a clustering type collaborative decision-making mechanism.

The invention discloses a tunnel non-uniform illumination adaptive image enhancement method and system, and relates to the technical field of image enhancement. The method comprises the following steps: acquiring a low-light / non-uniform illumination image in a tunnel monitoring scene and carrying out format standardization processing on the low-light / non-uniform illumination image; a plurality of complementary wavelet bases composed of Haar wavelets, Symlet-2 wavelets and biorthogonal wavelets are adopted, collaborative decomposition is carried out on the standardized image, and a low-frequency band and a high-frequency band are output; performing forward noise addition and reverse denoising optimization of dynamic parameter adjustment on the low-frequency band to realize global brightness equalization and noise suppression; high-frequency band details are strengthened through a linear repair framework without a nonlinear activation function, and key structure information is reserved; and performing inverse wavelet transform on the optimized low-frequency band and the repaired high-frequency band to generate an enhanced image, and transmitting the enhanced image to a target terminal or system. The tunnel non-uniform illumination problem is solved in a targeted manner, the image brightness balance and detail fidelity are improved, and the engineering application requirement of tunnel monitoring is met.

The application discloses a kind of iron polymetallic ore ore-induced anomaly extraction methods under the double-orthogonal wavelet base Brige-Massart strategy, it is related to geological exploration technical field.The main content includes: using the orthogonal wavelet base of multi-resolution analysis structure, complete orthogonal wavelet transform, complete decomposition, prediction and update;For the high-frequency strong interference noise caused by volcanic rock, intrusive rock and near-surface uneven body in gravity and magnetic data, using double-orthogonal wavelet base Brige-Massart strategy eliminates interference noise and keeps the original information of the anomaly caused by iron ore body;Test the actual effect of different wavelet base and denoising method on the anomaly caused by iron polymetallic ore body of different depth.The application further improves the signal extraction efficiency and precision of the anomaly caused by iron mine, linearly shifts the original signal by linear phase filtering, improves the symmetry of orthogonal wavelet, so as to reduce the signal distortion caused by volcanic rock and other high-frequency geological bodies.