55 votes
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Is deep learning killing image processing/computer vision?

On the top of this answer, you can see a section of updated links, where artificial intelligence, machine intelligence, deep learning or and database machine learning progressively step of the grounds ...
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25 votes

What is the difference between feature detectors and feature descriptors?

An interest point (key point, salient point) detector is an algorithm that chooses points from an image based on some criterion. Typically, an interest point is a local maximum of some function, such ...
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22 votes

Is deep learning killing image processing/computer vision?

First, there is nothing wrong with doing grad work in image processing or computer vision and using deep learning. Deep learning is not killing image processing and computer vision, it is merely the ...
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19 votes
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Why should an image be blurred using a Gaussian Kernel before downsampling?

An image "should not be blurred using a Gaussian Kernel" in general. This however can be a safe bet for a lot of basic image processing needs, and a smoothing is almost mandatory when you ...
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17 votes

What are the audio equivalents of images like "Lena", "Mandrill", and "Cameraman"?

The closest example I can think of is the beginning of Suzanne Vega's "Tom's Diner" which has been used for the mpeg-1 layer 3 development, and is still occasionally used to demo audio codecs.
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17 votes
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Why Is the Canny Edge Detection Used Instead of Sobel / Prewitt Edge Detection Before Hough Transformation?

Canny Edge Detection is considered to be a better (In False Alarm sense) edge detection than those you mentioned. This is, mainly, due to 2 steps: Non Maximum Suppression - Edges candidates which are ...
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17 votes
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Why real part of FFT converts image into rotation + original?

Let's say your image is given by $I(x,y)$. Then its Fourier transform is given by $$ I^f(\omega_x,\omega_y) = \int_x\int_yI(x,y)e^{j\omega_xx}e^{j\omega_yy}dxdy $$ Now you take the real part and ...
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  • 1,440
16 votes

What are the audio equivalents of images like "Lena", "Mandrill", and "Cameraman"?

Audio processing is a large field, but specifically in speech processing, an open database of samples known as Harvard Sentences is widely used. Harvard sentences are phonetically balanced collections ...
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16 votes
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Image Reconstruction:Phase vs. Magnitude

Figure 1.(c) shows the Test image reconstructed from MAGNITUDE spectrum only. We can say that the intensity values of LOW frequency pixels are comparatively more than HIGH frequency pixels. Actually, ...
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  • 3,559
16 votes
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Which image filter can be applied to remove gridded pattern from corrupt jpegs?

You can use a standard inpainting algorithm. These algorithms replace marked pixels in an image with the pixel values that surround these marked pixels. The challenge here is to detect the grid (my ...
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16 votes
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DSP or signal/image/data processing jokes

An airplane is leaving Warsaw (the capital of Poland), and gets caught in a terrible winter storm. The plane rolls, pitches and yaws. The crew is expecting the plane to crash or break up at any time. ...
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16 votes
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what does "derivative" means in image processing?

Look at the numbers in the filter kernel in just 1 dimension for simplicity. For a Sobel and Prewitt matrix you have something that roughly looks like this ...
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16 votes
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What is different between Euclidean distance and the Geodesic distance?

Simple: the Euclidean distance completely ignores the shape when finding a path from the start point to the end point while, for the geodesic distance, the path is constrained to be within the given ...
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14 votes
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$8 \times 8$ block matrix in JPEG image compression?

The lossy JPEG compression does not merely remove small coefficients in higher frequencies. It encodes them with a precision relative to a (relatively crude) visual perception model; most notably, ...
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14 votes
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What Is the Difference between Difference of Gaussian, Laplace of Gaussian, and Mexican Hat Wavelet?

Laplace of Gaussian The Laplace of Gaussian (LoG) of image $f$ can be written as $$ \nabla^2 (f * g) = f * \nabla^2 g $$ with $g$ the Gaussian kernel and $*$ the convolution. That is, the Laplace ...
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  • 1,077
14 votes
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Auto Detection of Rotation Angle on Arbitrary Image with Orthogonal Features

If I understand your method 1 correctly, with it, if you used a circularly symmetrical region and did the rotation about the center of the region, you would eliminate the region's dependency on the ...
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13 votes

Is deep learning killing image processing/computer vision?

No Deep Learning isn't killing Image Processing. You need huge datasets and lots of computational resources to do deep learning. There are plenty of applications where it is desirable to be able to do ...
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13 votes

Is deep learning killing image processing/computer vision?

Today we had a discussion with a friend of mine. It was a rainy day here in Munich, while a large portion of Europe was having a kind of sunny atmosphere. People were sharing photographs in social ...
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13 votes
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Why does this Moiré pattern look like this?

You'll need to understand the sampling theorem. In short, each signal has what we call a spectrum¹, which is the Fourier transform of the signal as it comes in time domain (if it is a time signal), or ...
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12 votes
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Accessing Maximum Value from a Singular Value Decomposed Matrix

The SVD Decompose the image into the (One way to look at it) many matrices. For instance, given an Image $ I $ its SVD is given by: $$ I = U S {V}^{T} = \sum_{i=1}^{\textrm{rank}(I)} {s}_{i} {u}_{i} {...
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12 votes
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Which Noise Reduction Algorithms Are Used in Commercial RAW Image Processors?

Common Approaches for Commercial Denoisers Commercial denoisers are different than what you'd see on most papers. While on papers the results are mostly using objective metrics (PSNR / SSIM) and are ...
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12 votes
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Python vs Matlab? Which one better for image processing?

[Comparison with cars at the end] For learning from scratch, I would not suggest a programming language alone, but instead the couple "teaching materials" (book, lecture notes) + "...
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10 votes
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When is a network called end-to-end training?

From feature extraction to learning the desired result, deep learning algorithms can act as full pipelines for solving tasks at hand. End-to-end learning usually refers to omitting any hand-crafted ...
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  • 5,225
10 votes
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Subpixel - what is it?

Images are technically limited to the original pixel resolution. Objects in an image are spatially quantized at this resolution. However, an edge for instance may be localized "between" native pixels. ...
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10 votes

DSP or signal/image/data processing jokes

In high school math class I finally got the courage up to ask the cute and brainy girl at the front row out on a date. She just looked at me with a discouraging face and as she waved her hand face ...
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10 votes

Peak Signal to Noise Ratio (PSNR) in Python for an Image

You can use cv2.PSNR like this example: import cv2 img1 = cv2.imread('img1.bmp') img2 = cv2.imread('img2.bmp') psnr = cv2.PSNR(img1, img2)
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10 votes
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How to Check Separability of 2D Filter / Signal / Matrix

Nilesh Padhi, Welcome to the DSP Community. The classic definition of separable means the data (2D) given by $ X \in \mathbb{R}^{m \times n} $ can be written as: $$ X = \sigma u {v}^{T} $$ Where $ \...
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10 votes
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Why Does the Median Filter Minimize the Absolute Value Error $L_1$ Cost Function?

Given a set of values $ {\left\{ {s}_{i} \right\}}_{i = 1}^{N} $, we're basically after: $$ \arg \min_{x} \sum_{i = 1}^{N} \left| {s}_{i} - x \right| $$ One should notice that $ \frac{\mathrm{d} \left ...
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10 votes
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Number of dimensions? Color image vs gray scale image? Colour video vs gray scale video? Especially in the context of MATLAB

Color images are usually modeled as a vector valued function of 2D: $$ I : \mathbb{R}^{2} \to \mathbb{R}^{3} $$ Namely for 2D coordinates input it outputs 3 values (RGB). Hence images are 2D functions....
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  • 41.3k
10 votes
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Universal bases (dictionary) for image compression

This is a great and interesting question. There are 2 ways to look at it, empirically and analytically. But before we start, a major detail is that when dealing with images we mainly talk about the ...
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