Handling Gaussian blur without deconvolution

Kostková, Jitka; Flusser, Jan; Lébl, Matěj; Pedone, Matteo

doi:10.1016/j.patcog.2020.107264

Cited by 22 publications

(13 citation statements)

References 44 publications

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“…It is worthy to mention that the factors associated with the image intensity like brightness, contrast, intensity and others have positive impact on the data collection instances when collected at different weather conditions. e Gaussian blur [15] is regarded as one of the computation parameter that helps in visualizing and simulating the effects of bad and hazy weather on the process of image acquisition. Furthermore, the positions of the camera and the images of the affected grape leaves are processed through the rotation transformations at different angles namely 90, 180 degrees, and 270 degrees using including horizontal and vertical symmetry operations.…”

Section: Data Augmentationmentioning

confidence: 99%

Detection of Deficiency of Nutrients in Grape Leaves Using Deep Network

Ali

Husnain

et al. 2022

Mathematical Problems in Engineering

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It is quite natural that the crops may be affected from a number of diseases due to many factors namely, change in climate, variations in environmental changings, deficiency of urea etc. Among these factors, the deficiency of the natural nutrients is one of the common reasons that may effect on the overall production of a certain crop. The grape leaves are one of crops that are affected by the deficiency of nutrients like Potassium, Magnesium, Nitrogen and Phosphorus. Furthermore, the effects of these nutrients may have similar disorders on the grape leaves like tilting off the leaf from edges, change in color, rusting off from the root etc. and it is hard to find the identify the nutrient which is likely to be deficient in the grape leaf. In order to ensure the good quality and high production, it is necessary to design an automated system that helps in classifying the affected grape leaf in any of the four classes namely, Potassium-deficient (K-deficient), Phosphorus-deficient (P-deficient), Nitrogen-deficient (N-deficient) or Magnesium-deficient (Mg-deficient). To achieve this target, we performed a series of experiment in which we first created a dataset of grape leaves affected from the deficiency of nutrients, from the crop fields in a controlled environment. The dataset is also augmented since the data instances were not in appropriate amount to achieve the negotiable results. After preprocessing, the Convolution Neural Network (CNN) classifier is used to achieve the average individual accuracies of 77.97%, 77.74%, 81.81% and, 78.09% for K-, Mg-, P- and N-deficient grape leaves, respectively using conventional training testing ratio and while for the same sequence individual accuracies achieved are 95.95%, 92.70%, 90.91% and , 94.76% using n-fold cross validation approaches on the original dataset. These accuracies were improved when these approaches are applied on the augmented dataset. The results were also compared with recent studies concluding that our proposed approach outperformed the previous studies. Our experimental results are equally applicable and beneficial when implemented on mobile devices for getting real-time results.

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Section: Data Augmentationmentioning

confidence: 99%

Detection of Deficiency of Nutrients in Grape Leaves Using Deep Network

Ali

Husnain

et al. 2022

Mathematical Problems in Engineering

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“…It can reduce the interference of the original noise on edge detection. Therefore, Gaussian blur transformation is used to reduce the level of image detail and noise interference, so that images can become smoother and easier to perform stereo matching [15,16]. Gaussian Blur transformation is defined as Eq.…”

Section: Gaussian Blur Transformationmentioning

confidence: 99%

An Improved Sum of Squared Difference Algorithm for Automated Distance Measurement

2021

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In recent years, with improvement of photoelectric conversion efficiency and accuracy, photoelectric sensor was arranged to simulate binocular stereo vision for 3D measurement, and it has become an important distance measurement method. In this paper, an improved sum of squared difference (SSD) algorithm which can use binocular cameras to measure distance of vehicle ahead was proposed. Firstly, consistency matching calibration was performed when images were acquired. Then, Gaussian blur was used to smooth the image, and grayscale transformation was performed. Next, the Sobel operator was used to detect the edge of images. Finally, the improved SSD was used for stereo matching and disparity calculation, and the distance value could be obtained corresponding to each point. Experimental results showed that the improved SSD algorithm had an accuracy rate of 95.06% when stereo matching and disparity calculation were performed. This algorithm fully meets the requirements of distance measurement.

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“…The main idea can also be expressed by the (51). In this regard, the works of Flusser et al [102][103][104][105] are remarkable.…”

Section: Robustness/invariance Optimizationmentioning

confidence: 99%

“…denoising and deblurring, are very challenging tasks. Such approach is, generally, slow, and unstable due to the restoration artifacts [102]. For the bruteforce path such as CNN, the lack of inherent invariance causes them to be very sensitive to noise and blurring operations not seen in the training.…”

Section: ) Recent Advance Of Robustness/invariance Optimizationmentioning

confidence: 99%

A Survey of Orthogonal Moments for Image Representation: Theory, Implementation, and Evaluation

Qi,

Zhang,

Wang

et al. 2021

Preprint

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Image representation is an important topic in computer vision and pattern recognition. It plays a fundamental role in a range of applications towards understanding visual contents. Moment-based image representation has been reported to be effective in satisfying the core conditions of semantic description due to its beneficial mathematical properties, especially geometric invariance and independence. This paper presents a comprehensive survey of the orthogonal moments for image representation, covering recent advances in fast/accurate calculation, robustness/invariance optimization, and definition extension. We also create a software package for a variety of widely-used orthogonal moments and evaluate such methods in a same base. The presented theory analysis, software implementation, and evaluation results can support the community, particularly in developing novel techniques and promoting realworld applications.

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Handling Gaussian blur without deconvolution

Cited by 22 publications

References 44 publications

Detection of Deficiency of Nutrients in Grape Leaves Using Deep Network

Detection of Deficiency of Nutrients in Grape Leaves Using Deep Network

An Improved Sum of Squared Difference Algorithm for Automated Distance Measurement

A Survey of Orthogonal Moments for Image Representation: Theory, Implementation, and Evaluation

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