transform_deconvolve() [1/2]

template<OperationReadyData DataType>

DataType MayaFlux::Yantra::transform_deconvolve	(	DataType &	input,
		const std::vector< double > &	impulse_to_remove,
		double	regularization,
		std::vector< std::vector< double > > &	working_buffer
	)

Deconvolution using frequency domain division (OUT-OF-PLACE) Useful for removing known impulse responses.

Template Parameters

DataType

OperationReadyData type

Parameters

input	Input data - will NOT be modified
impulse_to_remove	Impulse response to remove
regularization	Regularization factor for numerical stability
working_buffer	Buffer for operations (will be resized if needed)

Returns

Deconvolved data

Definition at line 486 of file ConvolutionHelper.hpp.

{
    auto [target_data, structure_info] = OperationHelper::setup_operation_buffer(input, working_buffer);
 
    auto deconvolution_op = [regularization](const Eigen::VectorXcd& input_fft,
                                const Eigen::VectorXcd& kernel_fft,
                                Eigen::VectorXcd& result_fft) {
        std::ranges::transform(input_fft, kernel_fft, result_fft.begin(),
            [regularization](const std::complex<double>& signal, const std::complex<double>& kernel) {
                double magnitude_sq = std::norm(kernel);
                if (magnitude_sq < regularization) {
                    return std::complex<double>(0.0, 0.0);
                }
                return signal * std::conj(kernel) / (magnitude_sq + regularization);
            });
    };
 
    working_buffer.clear();
    working_buffer.resize(target_data.size());
 
    for (size_t i = 0; i < target_data.size(); ++i) {
        working_buffer[i] = fft_convolve_helper(target_data[i], impulse_to_remove, deconvolution_op);
    }
 
    return OperationHelper::reconstruct_from_double<DataType>(working_buffer, structure_info);
}

References transform_deconvolve().

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