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Defocus blur detection based on transformer and complementary residual learning
Defocus blur detection (DBD), a technique for detecting defocus or in-focus pixels in a single image, has been widely used in various fields....
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Defocus blur detection via adaptive cross-level feature fusion and refinement
Convolutional neural networks have achieved competitive performance in defocus blur detection (DBD). However, due to the different receptive fields...
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Defocus Blur detection via transformer encoder and edge guidance
Defocus blur detection (DBD) aims to separate blurred and unblurred regions for a given image. Benefiting from the powerful extraction capabilities...
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NeRF-FF: a plug-in method to mitigate defocus blur for runtime optimized neural radiance fields
Neural radiance fields (NeRFs) have revolutionized novel view synthesis, leading to an unprecedented level of realism in rendered images. However,...
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Defocus blur detection using novel local directional mean patterns (LDMP) and segmentation via KNN matting
Detection and segmentation of defocus blur is a challenging task in digital imaging applications as the blurry images comprise of blur and sharp...
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Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space
Though modern microscopes have an autofocusing system to ensure optimal focus, out-of-focus images can still occur when cells within the medium are...
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Deep Depth from Focal Stack with Defocus Model for Camera-Setting Invariance
We propose deep depth from focal stack (DDFS), which takes a focal stack as input of a neural network for estimating scene depth. Defocus blur is a...
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United Defocus Blur Detection and Deblurring via Adversarial Promoting Learning
Understanding blur from a single defocused image contains two tasks of defocus detection and deblurring. This paper makes the earliest effort to...
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Single image defocus map estimation through patch blurriness classification and its applications
Depth information is useful in many image processing applications. However, since taking a picture is a process of projection of a 3D scene onto a 2D...
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Adjust Your Focus: Defocus Deblurring from Dual-Pixel Images Using Explicit Multi-Scale Cross-Correlation
Defocus blur is a common problem in photography. It arises when an image is captured with a wide aperture, resulting in a shallow depth of field....
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Leveraging Blur Information for Plenoptic Camera Calibration
This paper presents a novel calibration algorithm for plenoptic cameras, especially the multi-focus configuration, where several types of...
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Depth perception in single camera system using focus blur and aperture number
This article discusses a depth prediction model that takes advantage of rich interpretations. Profundity assessment is a basic interest for scene...
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Image enhancement and blur pixel identification with optimization-enabled deep learning for image restoration
Image enhancement is the process of enhancing specific aspects of an image, such as its borders or contrast. The procedure of restoring a destroyed...
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A zoom tracking algorithm based on defocus difference
The image clarity evaluation function was commonly used by the autofocus algorithm to evaluate the clarity of the image. And autofocus algorithms...
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A model-independent method for local blur estimation and its application to edge detection
Knowledge is hidden in images in form of objects, structures, patterns and their relationships, which are acquired through devices associated with...
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Super-Resolution of Defocus Thread Image Based on Cycle Generative Adversarial Networks
The dual camera calibration measurement method can realize low-cost and high-precision bolt dimension measurement by using two microscope cameras....
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Defocus Blur Detection via Depth Distillation
Defocus Blur Detection (DBD) aims to separate in-focus and out-of-focus regions from a single image pixel-wisely. This task has been paid much...
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Deblur and deep depth from single defocus image
In this paper, we tackle depth estimation and blur removal from a single out-of-focus image. Previously, depth is estimated, and blurred is removed...
