Dipan Mehta
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What Is the Relationship Between a Kalman Filter and Polynomial Regression?
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56 votes

1. There is a Difference in terms of optimality criteria Kalman filter is a Linear estimator. It is a linear optimal estimator - i.e. infers model parameters of interest from indirect, inaccurate and ...

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Image Shadow Removal Using OpenCV and Python
1 votes

OpenCV has many different Background subtraction models. If you use: cv2.BackgroundSubtractorMOG it will produce foreground without any shadows. If you use: cv2.BackgroundSubtractorMOG2 it will ...

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When does the laugh track kick in?
1 votes

Based on your observation, that spectrum of the signal is sufficiently distinguishable, you can use this as a feature to classify laughter from speech. There are many ways you can look at the ...

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What is limit on performance of edge-preserving filters for low signal-to-noise regimes?
0 votes

I am not sure if I am really answering your question correctly - but the point is, any linear filter by all means will do worse to preserve edges while removing noise. However, if only you must have ...

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Recognizing object of interest in object tracking using Lucas-Kanade method
2 votes

Tracking objects can be simple to complex depending on what type of background you have, whether the background is static or moving, whether the object is clearly distinguishable or can share similar ...

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MP3 Filterbank + MDCT: Why?
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3 votes

MP3 is a lossy compression which exploits -psychoacoustic masking. Basically, the human ear has a perception limitations in identifying sounds due to active processing as well as due to non-linear ...

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Physical significance of resolution in image processsing
1 votes

So the question really is, "what is a pixel?" A pixel when you access the data/sample of the image is just a number. The capturing device has generated this data represents the visible area on a ...

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Does every 8 by 8 DCT matrix have a valid (in range) IDCT?
4 votes

All images blocks that are applied by DCT matrix have a valid IDCT - i.e. they can always bring back original pixels and in general inverse transfer is theoretically as well as computationally viable. ...

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What is the optimal filter?
5 votes

The question is rather vague or inaccurate really; or I haven't understood it well. I would start with saying "there is no such a thing as a 'best' filter (for all use)". A filter is optimal only ...

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Fast method to decompress huffman and arithmetic encoded data
2 votes

For actual implementations take a look at (C) programming codes for decoders. Basically the process is simple, you create an abstraction such as bits = get_bits(n) Where, n is the n bits you want ...

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How to remove noise from this image without causing the crack to 'shrink'?
1 votes

Your problem is much less that of noise - rather that of clutter. (I may be completely wrong!) What you need to do is isolate the crank portion from everything else. This is essentially segmentation ...

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Do the DCT coefficients correspond to particular pixels?
7 votes

What I'm planning to do is to apply edge detection to obtain the locations/indices of the pixels and then get their corresponding DCT Coefficient As others stated in the comment - any pixel in ...

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What Resources Are Recommended for an Introduction to Signal Processing (DSP)?
18 votes

The below three are the best referred Text books on this subject. Discrete-Time Signal Processing, Prentice-Hall Signal Processing Series by Alan V. Oppenheim, Ronald W. Schafer, John R. Buck. ...

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Libraries for Voice Activity Detection (Not Speech Recognition)
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14 votes

In my answer to your that question, I had mentioned that Voice Activity Detection is a standard feature for codecs like G.729 and such others. You should look for reference encoders and decoders ...

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difference between mean filter and order statistic filter
0 votes

I would try to help you more than answering! OK - in simple terms mean filter is the low pass filter applied through averaging of a fixed window convoluted through the image. You can learn from here ...

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Texture-like measures for quantifying density of data in binary images
1 votes

One of the most obvious that comes to mind is MPEG-7's Edge Histogram Descriptor. In this, you divide the image into blocks and consider the edge pixels across different angles forming the complete ...

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Purpose of interleaving in OFDM systems
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7 votes

Interleaving is not specific to OFDM. It is an age old technique used for improving error correcting codes. Basically, most error correction coding techniques are good at suppressing bit-wise errors ...

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Finding filaments in high dimensional space
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You know that in a two dimensional plane two points form a line why a simple equation holds namely - $y = mx + c$ put the other way if dimensions are $x1$ and $x2$ than for a line to exist, the ...

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Embedded Image Processing System that sends photos to Smartphone via Bluetooth
1 votes

This question is more of a hardware setup. Books like Gonzalez will be more relevant when you have images as pixels and process them to transform to more desirable images. Here are the few tips: ...

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How do the motion vectors work in predictive coding for MPEG?
5 votes

To simplify your confusion - there two processes : 1. Motion estimation 2. Motion compensation Before we talk about the estimation, we should talk about the Motion compensation. Let say, the $ ...

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What are characteristics of shadows in an image given an outdoor setting from an image processing point of view?
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2 votes

Shadow has very specific properties that makes it very clear way of making it distinguishable from the regular object. A lot of work in the area of background subtraction and surveillance has been ...

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What are some good signal and image processing blogs worth following?
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33 votes

There are many for different subjects - Efg's algorithm collection : http://www.efg2.com/Lab/Library/ImageProcessing/index.html DSP Forum : http://www.dsprelated.com/ Data compression - http://...

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How should a moving average handle missing data points?
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5 votes

As a general impression, regression would work better in automatically fitting the missing points rather than a moving average filter you have chosen. If you use an AR (auto regressive filter) or ...

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How to decide whether to use AR or MA for smoothing data?
2 votes

MA (Moving Average) filter is a FIR filter. In general it is given in this form - $$ Y(n) = \sum { w_i * X(n-i) } $$ In inherently it is always stable. AR (Auto regressive) filter is an IIR ...

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Connecting edges detected by an edge detector
5 votes

This might not be complete solution, but will give you good direction. Basically, what is the key criteria of to say that edges match? That "locally" the gradient of the edge matches and to some ...

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Lip sync over IP
6 votes

Before going to IP, I would like to draw your attention to lip synchronization techniques used in broadcast domain. This is also one of the toughest ones because here not only you want to maintain a ...

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Video Compression - When would an average of the previous and next I or P frame be useful
Accepted answer
3 votes

Before elaborating anything, i would urge you to go through my answer here that simplifies some of the common confusions prevailing about motion vectors and estimations. Your essential question is - ...

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Exam Question - end-to-end delay from video capture to video playout
2 votes

The total delay is directly related to minimum delay that needs processing at encoder and decoder before which the first frame is ready to render at the receiver. The process of the transmission and ...

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How to do prediction using frequency domain data?
2 votes

An important NOTE: Since you are talking about frequency domain, it is implied that entire DFT spectrum is available and hence estimation is used for smoothing rather than future prediction. If ...

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What is the best method for merging time lapsed photos? Accessable from python(PIL)
1 votes

Given that The camera never moves and the scene is typcially static. you can apply a very simple technique of Temporal averaging. Assume an image sequence $I_t[x][y]$ where $t$ denotes the time of ...

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