Cubic Polishing Spline-Based Algorithms for Industrial Image Processing

Industrial image processing is a major technology in the fourth industrial revolution. In recent years, the spline method has gained more and more attention in image processing. To explore an efficient industrial image processing algorithm, this article proposes novel cubic polishing spline algorithms. The cubic polishing spline is a high precision spline algorithm that brings more degrees of freedom by adding nodes to better balance the local and global aspects. First, the direct and indirect cubic polishing spline transforms are used for the image interpolation filter. Then, we construct the least squares cubic polishing spline and pyramid approximation method with application to the image reconstruction and image scaling (image upscaling or downscaling). Next, the frequency domain cubic polishing spline lowpass filter and highpass filter are proposed, and the proposed schemes are applied to image smoothing and image sharpening, respectively. Finally, the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) and root mean square error (RMSE) evaluation metrics are used to illustrate the reconstruction effects, and experiments show that the algorithms proposed in this article can achieve better reconstruction results with better fidelity and competitiveness compared with other schemes.