The actual data size is 255, but this 255 is already a double type space storage, and no overflow will occur if it is added. The number of decimal places 0 is determined by the length of double data. For example, if the original value is 255, then it will be 255.0 after conversion. The original data is between 0 and 255, but after conversion, it is still 0 to 255. Double (IMG) is a simple data type conversion, which converts an unsigned integer to a double precision floating-point double, but the data size does not change. Here is a supplement to explain the difference between im2double() and double(). I2 = double(img)/255 % Uint8 is converted to double, which is the same as im2double I1 = im2double(img) % Convert image to double precision type (0 ~ 1) Img = imread(‘./1.jpg’) % Read in is Unit8 (0 ~ 255) data Therefore, it is necessary to convert the image to double format before operation. The image data read by Matlab is uint8, and the values in MATLAB are usually stored and calculated by double (64 bit). One byte unsigned integer can only store 255 data at most, so it is easy to overflow the image operation 2. For example, if the pixel size of a color image is 400 * 300 (height * width), the saved data matrix is 400 * 300 * 3, where each color channel value is between 0 and 255 Function ‘*’ is not defined for values of class ‘uint8’ When it is an RGB image, it stores it in an 8-bit RGB matrix. In detail, imread stores gray-scale images in an 8-bit matrix. Compared with the default MATLAB data type, double precision floating-point double (64 bits, 8 bytes), it can naturally save a lot of storage space The image stored in this way is called 8-bit image. The data saved after reading pictures in MATLAB is uint8 (8-bit unsigned integer, i.e. MATLAB image type conversion and uint8, double, im2double, im2uint8 and mat2gray and other instructions – Thomas can write – CSDN blog 1. If it is not converted, the calculation will overflow
I64 = double (I8)/255% uint is converted to double I2 = im2double (I1)% convert image I1 to double precision type (assuming graph matrix range 0-255) Therefore, it is necessary to convert the image to double format before operation, Therefore, the image data read in MATLAB is uint8, and the values in MATLAB are generally stored and calculated in double (64 bit). When it is an RGB image, it is stored in an 8-bit RGB matrix Imread stores gray images in an 8-bit matrix. In order to save storage space, matlab provides a special data type uint8 (8-bit unsigned integer) for image, and the image stored in this way is called 8-bit image MATLAB image processing on Unit8_ Baidu Knows Imshow pictures in MATLAB should be converted into uint8: 1 The problem is for the matrices t which are derived from ×= ☞12R, I should have a 3x1 matrix but the answers are 3x3 matrices.The image pixel data is processed in MATLAB
%since there are two rotation matrices, for each of them there are two %Estimation of P2 based on svd decomposition of E %putting the first camera as world reference = estimateFundamentalMatrix(matched_points_image1,matched_points_image2,'NumTrials',2000) įprintf("Finding the essential metrics because we don't know the R and T between two cameras whose took the pictures.\n")
Executing triangulation and building the 3D position.Since I don't have any information about the P2 (projection matrix of the second image), I have to use the Essential matrix to be able to retrieve the matrix R and T for the second camera.Find the matching point, and estimate the fundamental matrix F.I was able to derive the matrix K from the first image because the requirement of the project asked for the camera calibration matrix of that specific image.įor the 3D reconstruction, I have to follow these steps: The photos have different positions and angles. I have to reconstruct the 3D position of some visible features, which are visible on two images taken from a car.