WO2017193372A1 - 一种实现全景图像拼接的方法及系统 - Google Patents
一种实现全景图像拼接的方法及系统 Download PDFInfo
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- WO2017193372A1 WO2017193372A1 PCT/CN2016/082030 CN2016082030W WO2017193372A1 WO 2017193372 A1 WO2017193372 A1 WO 2017193372A1 CN 2016082030 W CN2016082030 W CN 2016082030W WO 2017193372 A1 WO2017193372 A1 WO 2017193372A1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/222—Studio circuitry; Studio devices; Studio equipment
- H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/222—Studio circuitry; Studio devices; Studio equipment
- H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
- H04N5/265—Mixing
Definitions
- the present invention relates to the field of image processing technologies, and in particular, to a method and system for implementing panoramic image stitching.
- the panoramic image is an important scene representation method.
- the direct method and the like can be directly obtained by using a panoramic camera such as a feature, but the equipment for shooting is usually expensive, and the camera needs to be accurately calibrated when photographing, and the utility is poor, and it is a low cost to obtain a panoramic image by ordinary camera image stitching. And a more flexible approach.
- the image stitching method is used to obtain the panoramic image. This method does not have too high requirements for the photographing equipment. An ordinary camera can be used. However, when the existing image stitching method is used for image stitching, it is inevitable that the stitching boundary will be Create stitching seams.
- the technical problem to be solved by the present invention is to provide a method and system for realizing panoramic image stitching.
- Feature extraction algorithm is used to extract image feature points of each synchronous image at the same time after pre-processing, extract feature points, and calculate feature vectors of the extracted feature points;
- the nearest neighbor matching algorithm is used to obtain the homography matrix between the frames of the synchronous images at the same time;
- the method further includes:
- the acquired real-time panoramic image is output to the user handheld terminal in real time.
- the preprocessing of the synchronized images of the same time at the same time includes:
- Each of the synchronized images converted at the same time is a grayscale image, and the grayscale image is subjected to denoising processing.
- the feature extraction algorithm performs image feature extraction on each synchronous image at the same time after the pre-processing, extracts feature points, and calculates feature vectors of the extracted feature points, including :
- the feature extraction algorithm is used to extract the image feature points of the synchronized images at the same time after the pre-processing, and the feature points are extracted, and the spot detection algorithm is used to simplify the description of the extracted feature points, and the calculation is performed.
- the feature vector of each feature point is described.
- the obtaining, according to the acquired homography matrix of the synchronization images of the same time, the panoramic image mosaic of the collected multiple synchronization image data, and obtaining the real-time panoramic image including:
- An image data collecting device configured to collect multiplexed synchronous image data, wherein each of the collected multiplexed synchronized image data has an overlapping area
- An image pre-processing device configured to pre-process each synchronous image at the same time collected by the synchronous image data collecting device
- the image feature point processing device is configured to perform image feature point extraction on each synchronous image of the same time preprocessed by the image preprocessing device by using a feature extraction algorithm, extract each feature point, and calculate the extracted image. a feature vector of each feature point;
- the image matrix processing device is configured to obtain, according to the feature vector of each feature point calculated by the image feature point processing device, the nearest neighbor matching algorithm, and acquire a homography matrix between frames corresponding to each synchronous image at the same time;
- the image splicing processing device is configured to perform framing of the panoramic image corresponding to the collected multiplexed synchronous image data according to the homography matrix of each synchronous image acquired at the same time acquired by the image matrix processing device, and obtain real-time image Panoramic image
- the image output device is configured to output the real-time panoramic image acquired by the image mosaic processing device to the user handheld terminal in real time.
- the image preprocessing apparatus includes:
- An image gradation converting device configured to convert the multiplexed synchronous image data collected by the image data collecting device into a grayscale image
- the image denoising processing device is configured to perform denoising processing on the grayscale image obtained by the image gradation converting device.
- the image feature point processing device includes:
- the image feature point extracting device is configured to perform image feature point extraction on each synchronous image denoised by the image denoising processing device by using a feature extraction algorithm, and extract each feature point;
- An image feature point simplification device for simplifying description of feature points extracted by the image feature point extraction device by using a spot detection algorithm
- the feature vector computing device is configured to calculate a feature vector of each feature point that is simplified by the image feature point simplification device.
- the image splicing processing device includes:
- An image splicing device configured to perform panoramic image splicing on the collected multiplexed synchronous image data according to a homography matrix between frames of each synchronous image acquired at the same time acquired by the image matrix processing device;
- the image stitching processing device is configured to use an image fusion algorithm to smooth the overlapping area of the image stitched by the image stitching device, eliminate the image stitching seam, and obtain a real-time panoramic image.
- the method for realizing panoramic image splicing provided by the present invention firstly collects multiplexed synchronous image data, wherein each of the collected multiplexed synchronized image data has an overlapping area, and then each of the synchronized images at the same time Performing pre-processing, and then using feature extraction algorithm to extract image feature points of each synchronous image at the same time after pre-processing, extracting feature points, and calculating feature vectors of the extracted feature points, and then according to The calculated feature vector of each feature point is obtained by using the nearest neighbor matching algorithm, and the homography matrix between the frames corresponding to each synchronous image at the same time is obtained, and then according to the obtained corresponding synchronous image corresponding frame at the same time.
- the homography matrix is used to perform panoramic image stitching on the collected multi-path synchronous image data to obtain a real-time panoramic image, and then the acquired real-time panoramic image can be output to the user handheld terminal in real time, including a mobile phone, a tablet computer, etc. Terminal equipment, so as to achieve the elimination of image stitching, to achieve panoramic image Seam display, while also achieving the real-time user can obtain a seamless panoramic image.
- the system application image data collecting device for realizing panoramic image splicing provided by the present invention first collects multiplexed synchronous image data, and an overlapping region exists between each image in the collected multiplexed synchronized image data, and then the image pre-processing device Preprocessing each synchronous image acquired at the same time collected by the synchronous image data collecting device, and then the image feature point processing device adopts a feature extraction algorithm to perform image on each synchronized image at the same time preprocessed by the image preprocessing device. Feature point extraction, extracting each feature point, and calculating the feature vector of each extracted feature point, and then the image matrix processing device adopts the nearest neighbor matching algorithm according to the feature vector of each feature point calculated by the image feature point processing device.
- the image splicing processing device correspondingly collects the homography matrix between the frames according to the synchronization images acquired by the image matrix processing device at the same time.
- Multi-channel sync image data to panoramic image stitching Obtaining a real-time panoramic image, and then the real-time panoramic image acquired by the image output processing device according to the image splicing processing device is output to the user's handheld terminal, including a mobile terminal, a tablet computer, and the like, in real time, thereby achieving elimination of the image mosaic seam and realizing the panoramic view.
- the seamless display of images also enables users to obtain seamless panoramic images in real time.
- FIG. 1 is a schematic diagram of a method for implementing panoramic image stitching according to the present invention
- FIG. 2 is a schematic diagram of a system for implementing panoramic image stitching according to the present invention.
- the present invention provides a method and system for realizing panoramic image splicing, which is applied to the field of image processing technology.
- the method for realizing panoramic image splicing according to the present invention includes first collecting multiplexed synchronous image data, and the collected multiplexed synchronized image data There is an overlapping area between each image, and then the synchronization images of the same time are preprocessed, and then the feature extraction algorithm is used to extract the image feature points of the synchronized images at the same time after preprocessing, and extract each Feature points, and calculating feature vectors of the extracted feature points, and then, according to the calculated feature vectors of the feature points, using the nearest neighbor matching algorithm to obtain the corresponding frames between the synchronized images of the same time And obtaining a real-time panoramic image by obtaining a real-time panoramic image according to the homography matrix between the frames of the acquired synchronous images at the same time, and obtaining the real-time panoramic image, and then obtaining the real-time panoramic image.
- the present invention provides a method of implementing panoramic image stitching.
- FIG. 1 is a schematic diagram of a method for splicing a panoramic image according to the present invention.
- S1 collecting multiplexed synchronous image data, where there is an overlapping area between each of the collected multiplexed image data;
- the nearest neighbor matching algorithm is used to obtain a homography matrix between frames corresponding to each synchronous image at the same time;
- S6 Output the acquired real-time panoramic image to the user handheld terminal in real time, including a handheld terminal device such as a mobile phone or a tablet computer.
- a handheld terminal device such as a mobile phone or a tablet computer.
- collecting multiple synchronized image data includes:
- the synchronization signal is generated, and the multi-channel camera is controlled to synchronously collect images, so as to ensure overlapping regions between the acquired synchronized images and collect multiple synchronized image data.
- the preprocessing of the synchronized images at the same time includes:
- Each of the synchronized images at the same time is converted into a grayscale image, and the grayscale image is subjected to denoising processing, and the denoising processing includes Gaussian filtering.
- the feature extraction algorithm is used to extract the image feature points of the synchronized images at the same time after the pre-processing, extract the feature points, and calculate the feature vectors of the extracted feature points, including:
- the feature extraction algorithm including the Gaussian Laplacian normalization algorithm is used to extract the image feature points of the synchronized images at the same time after preprocessing, and extract the feature points, using the spot detection algorithm (DOH).
- DOH spot detection algorithm
- the description of the extracted feature points is simplified, and the feature vectors of the feature points are calculated.
- the panoramic image is obtained by performing the panoramic image splicing on the acquired multiplexed image data according to the acquired homography matrix of the synchronized image at the same time, and obtaining the real-time panoramic image, including:
- the panoramic image is spliced to the collected multiplexed image data, and the image fusion algorithm is used to smoothly transition the image overlapping region to eliminate the image. Stitch stitching for real-time panoramic images.
- the present invention also provides a system for implementing panoramic image stitching.
- FIG. 2 is a schematic diagram of a system for implementing panoramic image stitching according to the present invention.
- the system 20 for implementing panoramic image stitching includes:
- the image data collecting device 201 is configured to collect multiplexed synchronous image data, and an overlap region exists between each of the collected multiplexed image data;
- the image pre-processing device 202 is configured to preprocess the synchronization images of the same time collected by the synchronous image data collection device 201;
- the image feature point processing device 203 is configured to perform image feature extraction on each synchronous image at the same time and preprocessed by the image preprocessing device 202 by using a feature extraction algorithm, extract each feature point, and calculate each extracted image.
- Feature vector of feature points
- the image matrix processing device 204 is configured to acquire, according to the feature vector of each feature point calculated by the image feature point processing device 203, the nearest neighbor matching algorithm, and acquire the homography matrix between the frames corresponding to each synchronous image at the same time;
- the image splicing processing device 205 is configured to perform splicing of the panoramic image according to the collected multiplexed image data according to the multiplexed image of each of the synchronized images acquired by the image matrix processing device 204 at the same time.
- the image output device 206 is configured to output the real-time panoramic image acquired by the image mosaic processing device 205 to the handheld terminal device of the user, including a mobile phone, a tablet computer, or the like.
- the image preprocessing device 202 includes:
- the image gradation conversion device 2021 is configured to convert the multiplexed image data collected by the image data collection device 201 into a grayscale image
- the image denoising processing device 2022 is configured to perform denoising processing on the grayscale image obtained by the image gradation converting device 2021, and the denoising processing includes Gaussian filtering.
- the image feature point processing device 203 includes:
- the image feature point extracting means 2031 is configured to perform image feature point extraction on each of the synchronized images denoised by the image denoising processing device 2022 by using a feature extraction algorithm including a Gaussian Laplacian normalization algorithm, and extracting the image feature points. Characteristic points;
- the image feature point simplification device 2032 is configured to simplify the description of the feature points extracted by the image feature point extraction device 204 by using the spot detection algorithm;
- the feature vector calculation means 2033 is for calculating feature vectors of the respective feature points which are simplified by the image feature point simplification means 2032.
- the image splicing processing device 205 includes:
- the image splicing device 2051 is configured to perform panoramic image splicing on the collected multiplexed synchronous image data according to the homography matrix between the frames of the synchronized images at the same time acquired by the image matrix processing device 204;
- the image stitching processing device 2052 is configured to use an image fusion algorithm to smooth the overlapping area of the image stitched by the image stitching device 2051, eliminate image stitching, and obtain a real-time panoramic image.
- the method and system for realizing panoramic image splicing of the invention can be applied to the panoramic monitoring of vehicle driving, and can be a vehicle driving recorder product, and the system for realizing panoramic image splicing can be seen in the automobile and can be seen outside, and is comprehensive. And when people are away from the car, they can also observe the situation around the car through handheld terminal devices such as mobile phones and tablets. Just like being there, there is a function that can be used in the event of an accident. The information at the time was recorded to prevent the information from being destroyed by external factors.
- the method and system for realizing panoramic image splicing of the invention can be adopted in the hardware aspect, including the main control chip is S3C6410 (ARM11) model, the image data acquisition device 201 can adopt Logitech C200, the resolution is 640*480, and the transmission interface adopts USB3. 0.
- the main control chip is S3C6410 (ARM11) model
- the image data acquisition device 201 can adopt Logitech C200
- the resolution is 640*480
- the transmission interface adopts USB3. 0.
- the invention realizes the method and system for splicing panoramic images.
- a part of the main control programming is written in C language, based on the S3C6410 main control parameter, and the program operation is performed under the Linux system, the liunx system is widely used.
- the open source operating system for embedded environment, the main goal of master programming is: can clearly read a few pictures, provide a data foundation for the image stitching algorithm design, and another part is Bluetooth-based communication programming, Some are designed for PC software.
- the framework of the Linux system we first convert the image into a grayscale image and then select the feature points. We use the normalized approximation of the Gaussian Laplacian to select the features in the image.
- the pressure sensing device can set a threshold.
- our main controller can take the first two of us. Ten minutes of video uploading to the server is used to save the scene of the accident, to prevent the video from being destroyed by the outside world, causing unnecessary losses.
- the method for realizing panoramic image splicing provided by the present invention firstly collects multiplexed synchronous image data, wherein each of the collected multiplexed synchronized image data has an overlapping area, and then each of the synchronized images at the same time Performing pre-processing, and then using feature extraction algorithm to extract image feature points of each synchronous image at the same time after pre-processing, extracting feature points, and calculating feature vectors of the extracted feature points, and then according to The calculated feature vector of each feature point is obtained by using the nearest neighbor matching algorithm, and the homography matrix between the frames corresponding to each synchronous image at the same time is obtained, and then according to the obtained corresponding synchronous image corresponding frame at the same time.
- the homography matrix is used to perform panoramic image stitching on the collected multi-path synchronous image data to obtain a real-time panoramic image, and then the acquired real-time panoramic image can be output to the user handheld terminal in real time, including a mobile phone, a tablet computer, etc. Terminal equipment, so as to achieve the elimination of image stitching, to achieve panoramic image Seam display, while also achieving the real-time user can obtain a seamless panoramic image.
- the system application image data collecting device for realizing panoramic image splicing provided by the present invention first collects multiplexed synchronous image data, and an overlapping region exists between each image in the collected multiplexed synchronized image data, and then the image pre-processing device Preprocessing each synchronous image acquired at the same time collected by the synchronous image data collecting device, and then the image feature point processing device adopts a feature extraction algorithm to perform image on each synchronized image at the same time preprocessed by the image preprocessing device. Feature point extraction, extracting each feature point, and calculating the feature vector of each extracted feature point, and then the image matrix processing device adopts the nearest neighbor matching algorithm according to the feature vector of each feature point calculated by the image feature point processing device.
- the image splicing processing device correspondingly collects the homography matrix between the frames according to the synchronization images acquired by the image matrix processing device at the same time.
- Multi-channel sync image data to panoramic image stitching Obtaining a real-time panoramic image, and then the real-time panoramic image acquired by the image output processing device according to the image splicing processing device is output to the user's handheld terminal, including a mobile terminal, a tablet computer, and the like, in real time, thereby achieving elimination of the image mosaic seam and realizing the panoramic view.
- the seamless display of images also enables users to obtain seamless panoramic images in real time.
Abstract
公开一种实现全景图像拼接的方法及系统，其方法包括采集多路同步图像数据，对同一时刻的各路同步图像进行预处理，采用特征提取算法对该进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量，根据该特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵，根据该获取到的图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，将该获取到的实时全景图像实时输出到用户手持终端，从而达到实现对图像拼接缝的消除，实现全景图像的无缝显示，同时还实现用户可以实时获取到无缝的全景图像。
Description
技术领域
本发明涉及图像处理技术领域，尤其涉及一种实现全景图像拼接的方法及系统。
背景技术
全景图像是一种重要的场景表示方法，在实际应用中主要有两种方式来获得，直接方法和图像拼接法。直接法使用特征的全景相机等器材可以直接获取，但是拍摄用的器材通常比较昂贵，而且拍照时需要精确地校准摄像机，实用性较差，而采用普通摄像机图像拼接获得全景图像是一种低成本而且比较灵活的方法。采用图像拼接的方法获取全景图像这种方式对拍照的器材没有太高的要求，可以使用普通的照相机，但是采用现有的图像拼接方法进行图像拼接时,在拼接的边界上,不可避免地会产生拼接缝。
发明内容
本发明要解决的技术问题是提供一种实现全景图像拼接的方法及系统。
本发明的目的在于提供一种实现全景图像拼接的方法，包括：
采集多路同步图像数据，所述所采集的多路同步的图像数据中的各幅图像之间有重叠区域；
对同一时刻的各路同步图像进行预处理；
采用特征提取算法对所述进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算所述提取得到的各特征点的特征向量；
根据所述计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵；
根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像。
其中，在根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像之后，还包括：
将所述获取到的实时全景图像实时输出到用户手持终端。
其中，所述对同一时刻的各路同步图像进行预处理，包括：
转换同一时间的各路同步图像为灰度图像，并对所述灰度图像进行去噪处理。
其中，所述采用特征提取算法对所述进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算所述提取得到的各特征点的特征向量，包括：
采用特征提取算法对所述进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，采用斑点检测算法简化对所述提取到的特征点的描述，并计算所述各特征点的特征向量。
其中，根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，包括：
根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，采用图像融合算法对图像重叠区域进行平滑过渡，消除图像拼接缝，获得实时全景图像。
本发明的目的在于还提供一种实现全景图像拼接的系统，包括：
图像数据采集装置，用于采集多路同步图像数据，所述所采集的多路同步的图像数据中的各幅图像之间有重叠区域；
图像预处理装置，用于对所述同步图像数据采集装置所采集到的同一时刻的各路同步图像进行预处理；
图像特征点处理装置，用于采用特征提取算法对经所述图像预处理装置预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算所述提取得到的各特征点的特征向量；
图像矩阵处理装置，用于根据所述图像特征点处理装置计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵；
图像拼接处理装置，用于根据所述图像矩阵处理装置所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对应采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像；
图像输出装置，用于根据所述图像拼接处理装置所获取到的实时全景图像实时输出到用户手持终端。
其中，所述图像预处理装置，包括：
图像灰度转换装置，用于转换所述图像数据采集装置所采集到的多路同步图像数据为灰度图像；
图像去噪处理装置，用于对经所述图像灰度转换装置转换后得到的灰度图像进行去噪处理。
其中，所述图像特征点处理装置，包括：
图像特征点提取装置，用于采用特征提取算法对经所述图像去噪处理装置去噪后的各路同步图像进行图像特征点提取，提取得到各特征点；
图像特征点简化装置，用于采用斑点检测算法简化对所述图像特征点提取装置所提取到的特征点的描述；
特征向量计算装置，用于计算经所述图像特征点简化装置简化描述后的各特征点的特征向量。
其中，所述图像拼接处理装置，包括：
图像拼接装置，用于根据所述图像矩阵处理装置所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接；
图像拼接缝处理装置，用于采用图像融合算法对经所述图像拼接装置拼接后的图像的重叠区域进行平滑过度，消除图像拼接缝，获得实时全景图像。
本发明所提供的实现全景图像拼接的方法，首先采集多路同步图像数据，该所采集的多路同步的图像数据中的各幅图像之间有重叠区域，接着对同一时刻的各路同步图像进行预处理，然后采用特征提取算法对该进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量，接着根据该计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵，然后根据该获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，接着可以将该获取到的实时全景图像实时输出到用户手持终端包括手机、平板电脑等手持终端设备，从而达到实现对图像拼接缝的消除，实现全景图像的无缝显示，同时还实现用户可以实时获取到无缝的全景图像。
本发明所提供的实现全景图像拼接的系统应用图像数据采集装置首先采集多路同步图像数据，该所采集的多路同步的图像数据中的各幅图像之间有重叠区域，接着图像预处理装置对同步图像数据采集装置所采集到的同一时刻的各路同步图像进行预处理，然后图像特征点处理装置采用特征提取算法对经图像预处理装置预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量，接着图像矩阵处理装置根据图像特征点处理装置计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵，然后图像拼接处理装置根据图像矩阵处理装置所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对应采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，接着图像输出装置根据图像拼接处理装置所获取到的实时全景图像实时输出到用户手持终端包括手机、平板电脑等手持终端设备，从而达到实现对图像拼接缝的消除，实现全景图像的无缝显示，同时还实现用户可以实时获取到无缝的全景图像。
附图说明
图1，为本发明实现全景图像拼接的方法的示意图；
图2，为本发明实现全景图像拼接的系统的示意图。
具体实施方式
本发明提供一种实现全景图像拼接的方法及系统，应用于图像处理技术领域，本发明实现全景图像拼接的方法包括首先采集多路同步图像数据，该所采集的多路同步的图像数据中的各幅图像之间有重叠区域，接着对同一时刻的各路同步图像进行预处理，然后采用特征提取算法对该进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量，接着根据该计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵，然后根据该获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，接着可以将该获取到的实时全景图像实时输出到用户手持终端包括手机、平板电脑等手持终端设备，从而达到实现对图像拼接缝的消除，实现全景图像的无缝显示，同时还实现用户可以实时获取到无缝的全景图像。
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
本发明提供一种实现全景图像拼接的方法。
请参见图1，图1为本发明实现全景图像拼接的方法的示意图，本发明实现全景图像拼接的方法，包括：
S1、采集多路同步图像数据，该所采集的多路同步的图像数据中的各幅图像之间有重叠区域；
S2、对同一时刻的各路同步图像进行预处理；
S3、采用特征提取算法对该进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量；
S4、根据该计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵；
S5、根据该获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像；
S6、将该获取到的实时全景图像实时输出到用户手持终端包括手机、平板电脑等手持终端设备。
其中，采集多路同步图像数据，包括：
产生同步信号，控制多路摄像机对图像进行同步采集，保证所采集的各幅同步图像之间有重叠区域，采集多路同步图像数据。
其中，对同一时刻的各路同步图像进行预处理，包括：
转换同一时间的各路同步图像为灰度图像，并对该灰度图像进行去噪处理，该去噪处理包括高斯滤波去躁。
其中，采用特征提取算法对该进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量，包括：
采用特征提取算法包括高斯拉普拉斯算子的归一化算法对该进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，采用斑点检测算法（DOH）简化对该提取到的特征点的描述，并计算该各特征点的特征向量。
其中，根据该获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，包括：
根据该获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接，采用图像融合算法对图像重叠区域进行平滑过渡，消除图像拼接缝，获得实时全景图像。
本发明还提供一种实现全景图像拼接的系统。
请参见图2，图2为本发明实现全景图像拼接的系统的示意图，本发明实现全景图像拼接的系统20，包括：
图像数据采集装置201，用于采集多路同步图像数据，该所采集的多路同步的图像数据中的各幅图像之间有重叠区域；
图像预处理装置202，用于对同步图像数据采集装置201所采集到的同一时刻的各路同步图像进行预处理；
图像特征点处理装置203，用于采用特征提取算法对经图像预处理装置202预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量；
图像矩阵处理装置204，用于根据图像特征点处理装置203计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵；
图像拼接处理装置205，用于根据图像矩阵处理装置204所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对应采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像；
图像输出装置206，用于根据图像拼接处理装置205所获取到的实时全景图像实时输出到用户手持终端包括手机、平板电脑等手持终端设备。
其中，图像预处理装置202，包括：
图像灰度转换装置2021，用于转换图像数据采集装置201所采集到的多路同步图像数据为灰度图像；
图像去噪处理装置2022，用于对经图像灰度转换装置2021转换后得到的灰度图像进行去噪处理，该去噪处理包括高斯滤波去躁。
其中，图像特征点处理装置203，包括：
图像特征点提取装置2031，用于采用特征提取算法包括高斯拉普拉斯算子的归一化算法对经图像去噪处理装置2022去噪后的各路同步图像进行图像特征点提取，提取得到各特征点；
图像特征点简化装置2032，用于采用斑点检测算法简化对图像特征点提取装置204所提取到的特征点的描述；
特征向量计算装置2033，用于计算经图像特征点简化装置2032简化描述后的各特征点的特征向量。
其中，图像拼接处理装置205，包括：
图像拼接装置2051，用于根据图像矩阵处理装置204所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接；
图像拼接缝处理装置2052，用于采用图像融合算法对经图像拼接装置2051拼接后的图像的重叠区域进行平滑过度，消除图像拼接缝，获得实时全景图像。
本发明实现全景图像拼接的方法及系统可以应用于车载行车全景监控，可以是车载行车记录仪产品，应用该实现全景图像拼接的系统能够坐在汽车里面就能看见外面的情况，而且是全方位的；并且当人们远离汽车的时候也能通过手持终端设备如手机、平板电脑等手持终端设备观测汽车周围的情况，就如同身临其境一样，还有一项功能就是能在意外发生的时候把当时的信息记录下来，避免信息被来自外界因素的破坏。
本发明实现全景图像拼接的方法及系统，在硬件方面，可以采用包括主控芯片是S3C6410（ARM11）型号，图像数据采集装置201可以采用罗技C200，分辨率是640*480，传输接口采用USB3.0。
本发明实现全景图像拼接的方法及系统，在软件基础框架搭建方面，一部分主控编程采用C语言编写，以S3C6410主控参数为基础，在Linux系统下进行程序的运算，liunx系统是一个被广泛的应用于嵌入式环境的开源操作系统，主控编程的预期目标为：能够清晰的读出几张图片，为图片的拼接算法设计提供数据基础，另一部分是以蓝牙为基础的通讯编程，还有一部分为上位机（APP）软件设计。在Linux系统框架下，我们将读入的图片首先进行一个灰度图片的转换，再进行特征点的选取，我们采用的是高斯拉普拉斯算子的归一化近似来选取图像中的特征点，然后通过DOH简化了SIFT算法中对特征点的描述，最后用最近邻匹配得到两幅图像中的匹配特征点，在图像融合方面，其实在得到变换矩阵之后，下一步是对图像进行拼接。犹豫各个摄像头光强、色彩上的差异和变换矩阵的误差，图像重叠区域会有明显的拼接缝，为了得到清晰的全景图，需要采用图像融合算法对重叠区域进行平滑过渡，消除拼接缝。图像融合算法的好坏在很大程度上决定了最终所呈现给观察者的图像的质量常见的图像融合算法有加权平均法，多分辨率融合法，两者算法在处理图像融合上都有着自己擅长的领域。我们应该取长补短的去使用这两种方法。SURF算法在保证了SIF算法的鲁棒性的基础上，提高了运算效率，减少了时间复杂度，。通过这些算法得到我们所需要的全景图像后，我们可以在显示屏幕上时时的观察外界发生情况。在程序中，我们还采用了无线传输模块，可以进行远距离的视频传输，采用了GPRS模块，通过4G网络进行上传视频数据到手机上。就可以在远处实时观察汽车周围的情况。并且还在车上安装了一个压力传感装置，当发生事故的一瞬间，压力传感装置可以设定一个阈值，在超过这个阈值的时候，我们的主控制器就可以把我们之前的前二十分钟的录像上传至服务器，用于保存事故现场的情况，避免录像被外界给破坏掉，造成不必要的损失。
本发明所提供的实现全景图像拼接的方法，首先采集多路同步图像数据，该所采集的多路同步的图像数据中的各幅图像之间有重叠区域，接着对同一时刻的各路同步图像进行预处理，然后采用特征提取算法对该进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量，接着根据该计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵，然后根据该获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对该采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，接着可以将该获取到的实时全景图像实时输出到用户手持终端包括手机、平板电脑等手持终端设备，从而达到实现对图像拼接缝的消除，实现全景图像的无缝显示，同时还实现用户可以实时获取到无缝的全景图像。
本发明所提供的实现全景图像拼接的系统应用图像数据采集装置首先采集多路同步图像数据，该所采集的多路同步的图像数据中的各幅图像之间有重叠区域，接着图像预处理装置对同步图像数据采集装置所采集到的同一时刻的各路同步图像进行预处理，然后图像特征点处理装置采用特征提取算法对经图像预处理装置预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算该提取得到的各特征点的特征向量，接着图像矩阵处理装置根据图像特征点处理装置计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵，然后图像拼接处理装置根据图像矩阵处理装置所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对应采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，接着图像输出装置根据图像拼接处理装置所获取到的实时全景图像实时输出到用户手持终端包括手机、平板电脑等手持终端设备，从而达到实现对图像拼接缝的消除，实现全景图像的无缝显示，同时还实现用户可以实时获取到无缝的全景图像。
需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或者操作之间存在任何这种实际的关系或者顺序。而且，术语“包含”、“包括”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系统要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个、、、、、、”限定的要素，并不排除在包括所述要素的过程、方法、物品、设备或者装置中还存在另外的相同要素。
对于本发明实现全景图像拼接的方法及系统，实现的形式是多种多样的。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。
Claims (9)
- 一种实现全景图像拼接的方法，其特征在于，包括：采集多路同步图像数据，所采集的多路同步的图像数据中的各幅图像之间有重叠区域；对同一时刻的各路同步图像进行预处理；采用特征提取算法对所述进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算所述提取得到的各特征点的特征向量；根据所述计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵；根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像。
- 如权利要求1所述的实现全景图像拼接的方法，其特征在于，在根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像之后，还包括：将所述获取到的实时全景图像实时输出到用户手持终端。
- 如权利要求1所述的实现全景图像拼接的方法，其特征在于，所述对同一时刻的各路同步图像进行预处理，包括：转换同一时间的各路同步图像为灰度图像，并对所述灰度图像进行去噪处理。
- 如权利要求3所述的实现全景图像拼接的方法，其特征在于，所述采用特征提取算法对所述进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算所述提取得到的各特征点的特征向量，包括：采用特征提取算法对所述进行预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，采用斑点检测算法简化对所述提取到的特征点的描述，并计算所述各特征点的特征向量。
- 如权利要求1或4所述的实现全景图像拼接的方法，其特征在于，根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像，包括：根据所述获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接，采用图像融合算法对图像重叠区域进行平滑过渡，消除图像拼接缝，获得实时全景图像。
- 一种实现全景图像拼接的系统，其特征在于，包括：图像数据采集装置，用于采集多路同步图像数据，所述所采集的多路同步的图像数据中的各幅图像之间有重叠区域；图像预处理装置，用于对所述同步图像数据采集装置所采集到的同一时刻的各路同步图像进行预处理；图像特征点处理装置，用于采用特征提取算法对经所述图像预处理装置预处理后的同一时刻的各路同步图像进行图像特征点提取，提取得到各特征点，并计算所述提取得到的各特征点的特征向量；图像矩阵处理装置，用于根据所述图像特征点处理装置计算得到的各特征点的特征向量，采用最邻近匹配算法，获取到同一时刻的各路同步图像对应帧间的单应性矩阵；图像拼接处理装置，用于根据所述图像矩阵处理装置所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对应采集到的多路同步图像数据进行全景图像拼接，获得实时全景图像；图像输出装置，用于根据所述图像拼接处理装置所获取到的实时全景图像实时输出到用户手持终端。
- 如权利要求6所述的实现全景图像拼接的系统，其特征在于，所述图像预处理装置，包括：图像灰度转换装置，用于转换所述图像数据采集装置所采集到的多路同步图像数据为灰度图像；图像去噪处理装置，用于对经所述图像灰度转换装置转换后得到的灰度图像进行去噪处理。
- 如权利要求7所述的实现全景图像拼接的系统，其特征在于，所述图像特征点处理装置，包括：图像特征点提取装置，用于采用特征提取算法对经所述图像去噪处理装置去噪后的各路同步图像进行图像特征点提取，提取得到各特征点；图像特征点简化装置，用于采用斑点检测算法简化对所述图像特征点提取装置所提取到的特征点的描述；特征向量计算装置，用于计算经所述图像特征点简化装置简化描述后的各特征点的特征向量。
- 如权利要求6或8所述的实现全景图像拼接的系统，其特征在于，所述图像拼接处理装置，包括：图像拼接装置，用于根据所述图像矩阵处理装置所获取到的同一时刻的各路同步图像对应帧间的单应性矩阵，对所述采集到的多路同步图像数据进行全景图像拼接；图像拼接缝处理装置，用于采用图像融合算法对经所述图像拼接装置拼接后的图像的重叠区域进行平滑过度，消除图像拼接缝，获得实时全景图像。
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