convolution

I want to perform a simple 2D image convolution but my kernel is even-sized. Which indices I should pick for my kernel center? I tried googling for an answer and looking existing codes. People usually center their kernel so there would be one sample more before the new 0. So, if we have a 4x4 kernel the centered indices should be -2 -1 0 +1 . Is that correct? And if it is, why is that so? Can someone explain why -2 -1 0 +1 is correct while -1 0 +1 +2 is not? Keep in mind that I want to perform the convolution without using FFT. If I understand your question correctly, then for even sized

The goal is trying to using a customize weight on the first layer of model to full fill the function of highpass filter---make the first layer of Model is the same as the high pass filter to the image. 1.first, the similar solution will be: using a high pass filter in the image processing, and generate a new image, and use it in the model. ---this is have to use the image processing, which is cost of time. 2.I want to set the a layer of Conv2D , which is also able to high pass the image. with a custom filter( as a intializer). the basic is that the filter and the conv2D is both using

I am using convolution neural network. My data is quite imbalanced, I have two classes. My first class contains: 551,462 image files My second class contains: 52,377 image files I want to use weighted_cross_entropy_with_logits , but I'm not sure I'm calculating pos_weight variable correctly. Right now I'm using classes_weights = tf.constant([0.0949784, 1.0]) cross_entropy = tf.reduce_mean(tf.nn.weighted_cross_entropy_with_logits(logits=logits, targets=y_, pos_weight=classes_weights)) train_step = tf.train.AdamOptimizer(LEARNING_RATE, epsilon=1e-03).minimize( cross_entropy , global_step=global

OpenCV has the matchTemplate() function, which operates by sliding the template input across the output, and generating an array output corresponding to the match. Where can I learn more about how to interpret the six TemplateMatchModes ? I've read through and implemented code based on the tutorial , but other than understanding that one looks for minimum results for TM_SQDIFF for a match and maximums for the rest, I don't know how to interpret the different approaches, and the situations where one would choose one over another. For example (taken from the tutorial) res = cv.matchTemplate(img

I'm using a convolution matrix for sharpness in PHP GD and I want to change the sharpness "level" . Where would I make changes to this if I want to make it more or less sharp ? $image = imagecreatefromjpeg('pic.jpg'); $matrix = array( array(0, -1, 0), array(-1, 5, -1), array(0, -1, 0) ); imageconvolution($image, $matrix, 1, 0.001); header("Content-type: image/jpeg"); imagejpeg($image); try looking on http://www.gamedev.net/reference/programming/features/imageproc/page2.asp There are lots of examples on the web, but as a rule of thumb you may try these params first in GIMP or PS or any other