Highlight removal for camera captured documents based on image stitching

Jiao, Jile; Wang, Fan; Sun, Jun; Naoi, Satoshi

doi:10.1109/icsp.2016.7877950

Cited by 8 publications

(8 citation statements)

References 15 publications

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“…However, if LPF2 (Figure 15) is rotated (0°-180°), light reflection is suppressed (97%) when the angle of rotation (LPF2) is 90° as shown in Figure 18. The reason is that if the light reflection intensity (IEP) becomes cos290° as shown in Equations ( 7)- (10), when the rotation angle of F1 is 0° as shown in Figure 10, F2 has an orthogonal relationship, so that the magnetic field (MT) is offset and the electric field (ET) disappears inversely. In Figure 19, the captured images were simulated using the region of interest (ROI) program.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…F1 is fixed and F2 is rotated relatively such that the specular reflection is eliminated effectively. If the direction angle (r1) of the F1 filter becomes 0° and the direction angle (r2) of the F2 filter is changed, the intensities of Vin and Hin passing through the filter are equal to those calculated by Equations ( 7)- (10) in P3.…”

Section: How To Eliminate Occurrence Of Specular Reflectionmentioning

confidence: 99%

“…To address this issue, several methods for suppressing specular reflection have been previously reported; however, research cases are still lacking [ 9 , 10 ]. Specular reflection is commonly minimized by adjusting the camera’s orientation angle in medical practice.…”

Section: Introductionmentioning

confidence: 99%

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Reduction of Specular Reflection Based on Linear Polarization Control for Fluorescence-Induced Diagnostic Evaluation

et al. 2022

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The primary goal of cancer surgery is to completely eliminate tumors. A real-time diagnostic method uses a fluorescence contrast agent and a surgical microscope to assess the status of tumor resection and the patient’s blood circulation. The biggest problem in imaging diagnostics using a microscope is the specular reflection phenomenon. While observing a lesion, the observation field may be obstructed due to specular reflection, making it difficult to obtain accurate results during the diagnostic process. Herein we propose a method to reduce specular reflection during tumor diagnosis by introducing a linearly polarized filter for a surgical microscope system. The method of angular direction adjustment of the filter ensures that only the horizontally polarized light passes through it, thereby obstructing the specular reflection. As a result of removing specular reflection, clear images were obtained at 90° and 270°. This experiment was conducted using phantoms and animals. Our results prove that the proposed method can be applied to imaging cameras used in internal medicine, surgery, and radiology for diagnosis.

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Section: Experiments Resultsmentioning

confidence: 99%

Section: How To Eliminate Occurrence Of Specular Reflectionmentioning

confidence: 99%

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Reduction of Specular Reflection Based on Linear Polarization Control for Fluorescence-Induced Diagnostic Evaluation

et al. 2022

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“…The result of these lighting aberrations is seen as temporal inconsistency and color flickering. 23,24 Recent efforts, such as those by Daher et al, 25 have tried to harness temporal data using traditional nonlearning methods to detect SR regions. However, their limited accuracy in SR detection causes temporal-aware generative adversarial models to unintentionally include undetected SR from other regions, resulting in noisy reconstructions.…”

Section: Related Workmentioning

confidence: 99%

“…A significant drawback of simple replacement approaches (e.g., homography transform), however, is that the restored SR regions do not have the same brightness of color as the surrounding area due to lighting inconsistencies caused by camera or light source movement from one frame to another. The result of these lighting aberrations is seen as temporal inconsistency and color flickering 23 , 24 . Recent efforts, such as those by Daher et al., 25 have tried to harness temporal data using traditional nonlearning methods to detect SR regions.…”

Section: Related Workmentioning

confidence: 99%

SpecReFlow: an algorithm for specular reflection restoration using flow-guided video completion

Yin,

Eimen,

Moyer

et al. 2024

J. Med. Imag.

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Specular reflections (SRs) are highlight artifacts commonly found in endoscopy videos that can severely disrupt a surgeon's observation and judgment. Despite numerous attempts to restore SR, existing methods are inefficient and time consuming and can lead to false clinical interpretations. Therefore, we propose the first complete deep-learning solution, SpecReFlow, to detect and restore SR regions from endoscopy video with spatial and temporal coherence.Approach: SpecReFlow consists of three stages: (1) an image preprocessing stage to enhance contrast, (2) a detection stage to indicate where the SR region is present, and (3) a restoration stage in which we replace SR pixels with an accurate underlying tissue structure. Our restoration approach uses optical flow to seamlessly propagate color and structure from other frames of the endoscopy video.Results: Comprehensive quantitative and qualitative tests for each stage reveal that our SpecReFlow solution performs better than previous detection and restoration methods. Our detection stage achieves a Dice score of 82.8% and a sensitivity of 94.6%, and our restoration stage successfully incorporates temporal information with spatial information for more accurate restorations than existing techniques.Conclusions: SpecReFlow is a first-of-its-kind solution that combines temporal and spatial information for effective detection and restoration of SR regions, surpassing previous methods relying on single-frame spatial information. Future work will look to optimizing SpecReFlow for real-time applications. SpecReFlow is a software-only solution for restoring image content lost due to SR, making it readily deployable in existing clinical settings to improve endoscopy video quality for accurate diagnosis and treatment.

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Specular Reflection Detection and Substitution: A Key for Accurate Medical Image Analysis

Oak

Iyer

2019

Lecture Notes in Electrical Engineering

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Highlight removal for camera captured documents based on image stitching

Cited by 8 publications

References 15 publications

Reduction of Specular Reflection Based on Linear Polarization Control for Fluorescence-Induced Diagnostic Evaluation

Reduction of Specular Reflection Based on Linear Polarization Control for Fluorescence-Induced Diagnostic Evaluation

SpecReFlow: an algorithm for specular reflection restoration using flow-guided video completion

Specular Reflection Detection and Substitution: A Key for Accurate Medical Image Analysis

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