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Application of spatial-domain convolution/deconvolution transform for determining distance from image defocus

机译:应用空间域卷积/解卷积变换确定距图像散焦的距离

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Abstract: per describes the application of a newSpatial-Domain Convolution/Deconvolution transform (Stransform) for determining distance of objects andrapid autofocusing of camera systems using imagedefocus. The method of determining distance, named STM,involves simple local operations on only a few (about 2to 4) images and it can be easily implemented inparallel. STM has been implemented on an actual camerasystem named SPARCS. Experiments on the performance ofSTM and their results on real- world objects arepresented. The results indicate that STM is useful inpractical applications. The utility of the method isdemonstrated for rapid autofocusing of electroniccameras. STM is computationally more efficient thanother methods, but for our camera system, it issomewhat less robust in the presence of noise than aFourier transform based approach. STM is a usefultechnique in many applications such as rapidautofocusing.!23
机译:摘要:每篇都描述了一种新的空间域卷积/解卷积变换(Stransform)在确定对象距离和使用图像散焦快速实现相机系统自动对焦方面的应用。确定距离的方法称为STM,它仅对几个(大约2至4个)图像进行简单的局部操作,因此可以轻松地并行实现。 STM已在名为SPARCS的实际相机系统上实现。展示了STM性能的实验及其在实际对象上的结果。结果表明STM是有用的实际应用。示出了该方法的实用性以用于电子相机的快速自动聚焦。 STM在计算上比其他方法更有效,但对于我们的相机系统,在存在噪声的情况下,它的健壮性要比基于傅立叶变换的方法要强一些。 STM是许多应用中的有用技术,例如快速自动对焦。23

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