In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to many imaging applications that suffer from optical imperfections. Despite numerous deconvolution methods that blindly estimate blurring in either inclusive or exclusive forms, they are practically challenging due to high computational cost and low image reconstruction quality. Both conditions of high accuracy and high speed are prerequisites for high-throughput imaging platforms in digital archiving. In such platforms, deblurring is required after image acquisition before being stored, previewed, or processed for high-level interpretation. Therefore, on-the-fly correction of such images is important to avoid possible time delays, mitigate computational expenses, and increase image perception quality. We bridge this gap by synthesizing a deconvolution kernel as a linear combination of finite impulse response (FIR) even-derivative filters that can be directly convolved with blurry input images to boost the frequency fall-off of the point spread function (PSF) associated with the optical blur. We employ a Gaussian low-pass filter to decouple the image denoising problem for image edge deblurring. Furthermore, we propose a blind approach to estimate the PSF statistics for two Gaussian and Laplacian models that are common in many imaging pipelines. Thorough experiments are designed to test and validate the efficiency of the proposed method using 2054 naturally blurred images across six imaging applications and seven state-of-the-art deconvolution methods.

中文翻译：

---

用于自然成像的卷积去模糊。

在本文中，我们以单次卷积滤波的形式提出了一种新颖的图像去模糊设计，可以直接与自然模糊的图像进行卷积以进行复原。对于许多遭受光学缺陷的成像应用来说，光学模糊的问题是一个普遍的缺点。尽管有许多反卷积方法盲目地以包含或排除形式估计模糊，但是由于高计算成本和低图像重建质量，它们实际上具有挑战性。高精度和高速度都是数字归档中高吞吐量成像平台的先决条件。在这样的平台中，图像采集后需要对图像进行去模糊处理，然后再进行存储，预览或处理以进行高级解释。因此，对此类图像进行即时校正对于避免可能的时间延迟，减轻计算费用并提高图像感知质量非常重要。我们通过将反卷积内核合成为有限冲激响应（FIR）偶数导数滤波器的线性组合来弥合这一差距，该滤波器可以直接与模糊输入图像进行卷积，以增强与之相关的点扩展函数（PSF）的频率下降光学模糊。我们采用高斯低通滤波器来解耦图像去噪问题，以实现图像边缘去模糊。此外，我们提出了一种盲法来估计两个高斯模型和拉普拉斯模型的PSF统计量，这在许多成像管线中都很常见。