Fuzzy image processing solution

There are many reasons for image blurring, and blurred images caused by different reasons require different methods for processing. From a technical point of view, fuzzy image processing methods are mainly divided into three categories, namely image enhancement, image restoration and super-resolution reconstruction. This article will cut into the analysis from these three aspects.

Intelligent device management technology is a device management service that utilizes system management platform software. It continuously monitors all monitoring devices, including cameras, pan/tilt, encoders, and system servers. When a fault is discovered, it can be alerted in various ways. , prompt maintenance personnel to dispose of in time. A system can deploy multiple device management servers according to the network topology, and perform real-time inspections on devices in a sub-area. This can greatly improve the maintenance efficiency of the system. When the device fails, it should be no more than 10 minutes. It is monitored and alerted.

The goal of building

This program intends to apply advanced machine learning and computer vision technology to simulate the human visual system. It is common for snowflake, scrolling, blur, color cast, picture freeze, gain imbalance and pan/tilt control of the front-end camera of a city's public security image resource. Camera failure and malicious occlusion and destruction of the monitoring device's illegal behavior to make accurate judgments, and automatically record all test results, generate reports. So that users can easily maintain the city public security image resource system.

Technical route

The video fault is divided into eight types: missing video signal, abnormal video resolution, abnormal video brightness, video noise, video snow, video color cast, picture freeze, and PTZ motion out of control. Among them, the video signal is missing. With the extensive construction of “Safe City”, a large number of video surveillance systems have been built in major cities. Although the monitoring system has been widely used in public places such as banks, shopping malls, stations and traffic intersections, In the public security work, due to the limitation of equipment or other conditions, the image playback after the occurrence of the case has the problem that the image is not clear and the data is incomplete, which cannot provide effective clues for the timely detection of the case. Frequently, the suspect's facial features are unclear, difficult to identify, and the suspect vehicle license plate is illegible and unrecognizable. This has caused great trouble for the public security department to solve the case and obtain evidence from the court. With the promotion of safe cities and the further advancement of various monitoring systems in various places, such problems will become more and more prominent.

Causes of blurred images

There are many reasons for image blurring, such as inaccurate focus, aberrations in the optical system, relative motion during imaging, atmospheric turbulence, low illumination, and ambient random noise. In addition, the encoding and decoding of images and the transmission process may cause further blurring of the image. In general, the main reasons for image blur are as follows:

· improper lens focus, camera malfunction, etc.;

· Transmission too far, video line aging, environmental electromagnetic interference, etc.;

· The camera cover window or lens is dirty, obstructed, etc.

· Harsh, dust, rain and snow, and other harsh environmental impacts;

· Blurring caused by video compression algorithms and transmission bandwidth causes;

· Low resolution camera, undersampled imaging;

· The limit resolution of the optical lens and the blur caused by the camera mismatch;

· Motion blur caused by moving objects in high-speed motion;

......

Fuzzy image common solution

For fuzzy image processing technology, domestic universities and scientific research institutions have been studying these theories and applications many years ago, and related literature has also been published, and some good applications have been achieved. Cognitech software in the United States is a mature fuzzy image recovery application. It has been used for many years in the US FBI and other law enforcement agencies. The recovered images can be directly used as forensic evidence. Visible image processing technology has been achieved. Quite practical application.

Image Processing

As mentioned above, there are many reasons for image blurring. To achieve better processing results, blurring caused by different reasons often requires different processing methods. From a technical point of view, fuzzy image processing methods are mainly divided into three categories, namely image enhancement, image restoration and super-resolution reconstruction.

Image enhancement

Many traditional image algorithms can reduce the degree of image blur, such as image filtering, geometric transformation, contrast stretching, histogram equalization, spatial sharpening, brightness uniformity, morphology, color processing, and so on. In a nutshell, these algorithms are relatively mature and relatively simple. However, for a specific fuzzy image, it is often necessary to combine one or more of the above algorithms to match the different parameters to achieve the desired effect. The combination of these algorithms and parameters is further developed into specific enhancement algorithms, such as "image defogging" algorithm, "image denoising" algorithm, "image sharpening" algorithm, "image dark detail enhancement" algorithm and so on. These algorithms improve image sharpness to varying degrees and greatly improve image quality.

The algorithm of image defogging can be realized by using algorithms such as morphology, image filtering and color processing. Figure 1 is the actual use effect of a defogging algorithm. There are many similar image enhancement algorithms, which are not listed one by one.

Image Processing

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