Key Program of National Natural Science Foundation of China (No.61333011);National Natural Science Foundation of China (No.61371064, No.61273075, No.61503206)
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.