Light Field Reconstruction Based on Wavelet Transform and Sparse Fourier Transform
ZHOU Guang-fu1, WEN Cheng-lin1, GAO Jing-li2
1. School of Automation, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China;
2. College of Electrical Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
With the development of computer graphics and computer vision technology,light field comes into sight and is rapidly applied in various fields.However,the acquisition of the light field needs a large amount of pictures,which has the characteristics of large data and high cost.So how to use a small amount of data to obtain the light field has been paid more and more attention,and a lot of work has been done.To address the above problems,a new method of light field reconstructing is proposed,which combines with wavelet transform and sparse Fourier transform by using sparseness of light field in angle domain.First,we use multi-resolution analysis characteristic of wavelet transform,and the original image can be decomposed into four sub-frequency images through wavelet transform.Then the frequency positions of four sub-frequencies are separately recovered through the Fourier slice theorem,and their two-dimensional angle spectrum are further obtained,respectively.Finally,the light field is obtained by combining the two-dimensional angle spectrum of each sub-frequency image and making inverse wavelet transform.In the proposed method,the original image is decomposed into four sub-images by using wavelet transform,and the sub-images are reconstructed respectively.This not only reduces the complexity of our method and greatly reduces the running time of our method,which provides the basis for the wide application of the light field,but also our method effectively inhibits the window effect by comparing to only using sparse Fourier algorithm,so that the reconstruction result is more accurate.In addition,the method can effectively improve problem of small frequency leakage in off-grid recovery by separating high frequency and low frequency information,and further improves the reconstruction results.In the end,the effectiveness of the algorithm is verified by simulation.
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2017, Vol. 45 
