Smoothing Spatial Filters in digital image processing

In this video, we talk about Smoothing Spatial Filters in digital image processing.
This video also talks about box filters, weighted average filters, Gaussian filters, median filters, min and max filters which come under linear and non-linear Smoothing filters.
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You're an amazing instructor. Simple & clear explanation, perfect understandable English, and straight to the point! Thank you for your effort.

[@020hamza2]

Your way of teaching is just perfect because you teach theory then numericals in proper sequence.

[@manjuchakraborty3945]

Sounds wierd but I love your voice.. ahem ahem..focus on the topic..

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[@vaibhavagarwal8899]

Yes it sounds weird dude please don't everh

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@@vaibhavagarwal8899 he's not wrong though. She even liked his comment.

[@saadtahsan]

I imagine you as my girlfriend who is teaching me! It helps me to focus more lol. Don't take it otherwise. May God bless you

[@collegefriendly]

Whatever helps you focus😂

[@saadtahsan]

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[@harshavantaku7003]

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[@collegefriendly]

Thank you😊

[@gursimartakkar537]

same here buddy

[@mohdarsalan794]

Thanks alot. Your voice is very melodious.

[@amvsekai]

Clear and concise explanation Thanks a lot💙🙏

[@alinatik35]

Straight to the point .......... You just solved my problem ............. I LOVE YOU thank you sooooo much ....🌹

[@SARDAR_EDITS]

Hi, thanks for the tutorial, they are really helpful, wish you could do some more examples on Filters

[@sukulalmundari4880]

Thank u madam. Madam, one request make a video for sharpening filter ....

[@kalirossi920]

Great video, really helped me understand filtering!

[@hitmoviesandwebseries4690]

Thank you ❤️ Kal Mera paper h You thought very well

[@عبداللهالشرعبي-ي6و]

A great and very distinctive explanation

[@adityabhargava927]

Made such a difficult topic soo easy to understand

[@collegefriendly]

Thank you so much😊

[@JyotiSharma-bt6tu]

Thank you very much ma'am these notes are very helpful.

[@ankurjyotichakrabarty]

saved me from semester exam :)

[@rajasekhar5982]

Very nice explanation .... Thank you very much

[@sunilshetty7268]

The video was really helpful, I would request you to make a video on the Laplace filter, thanks.

[@human_being9]

Thanks a lot sister, your videos are extremely helpful for me, and your voice is so beautiful.

[@sahilmakandar773]

Can you please explain in image size reduction how this interpolations will work(nearest, bilenear, bicubic). It will help a lot

[@bilalislam9869]

thank you mam , really helped me understand filters

[@stanlyvarghese9048]

thank you ma'am

[@devesh096]

Thank You So Much For The Videos.

[@ZohaJaved795]

Can you please do question on gaussian filter as well??

[@rimpidebnath8450]

Amazing. Just perfect!

[@coreygates1162]

thank you!!! very easy to follow , great job!!

[@ysf2143]

When we change the center pixel in both box and weighted filter, does the 6 become 5 or we should subtract (6-5) so the center becomes 1 ?

[@sreejithcs9443]

6 becomes 5

[@prasadpusalkar123]

great explanation, nice and crisp.

[@020hamza2]

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[@NourHmuser]

maam why you consider 2*2 as 6 not 7? we start rank of matrix from 0?

[@WaleedAhmed-no8yl]

great explanation nice work ma'am

[@AritraPain-pt7lq]

Please give me a book recommendation for this dip subject🎉

[@pamp3657]

Good video. Thank you.

[@chandnithakkar-j3i]

can you please explain the difference between box filter and average filter because we are getting same answer only difference i see is the use of different mask

[@anirudhmenon9099]

ma'am what about gaussian filter

[@DarrylGaming598]

I want to ask, the answer from the box/mean filter is 4.66 and rounded to 5. Why is the answer from the weighted average filter is 5.0625 and not rounded to 6?

[@rohanwarghade7111]

coz its is not 5.5

[@sanjyotpatil7]

thank u so much mam....excellent...can u share the written notes...

[@adityanath8946]

Really helped a lot

[@AliZia-k5f]

thanku mam

[@sahilmakandar773]

Great video

[@bhagyashribhashkar]

Thank you mam❤️

[@suntech7094]

perfect

[@ambikeshwarclasses6058]

Thanks a lot

[@abhinavbest2553]

Your voice is beautiful

[@roshanantony7467]

awesome, keep it up

[@arun3151997]

please post more!

[@sawsanasjea4828]

Very good , thnks. Can we get the slides as pdf, please.

[@m.d.r3086]

thanks for explaining, I need the lectures pdf plz

[@mihiragarwal1269]

Thanks fr the video😍

[@collegefriendly]

Welcome😊

[@vishnunair5853]

thank u didi

[@VinayKumar-dd7tt]

Mam which book you are following, please reply

[@jashanbhayana8089]

can somebody tell the role of surrounding numbers of the matrix?

[@gursimartakkar537]

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[@pranjalsoni2874]

2:20 wow

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[@birukasrat5234]

thanks a lot, I am from Ethiopia. how can I get your notes

[@collegefriendly]

Thanks. I am afraid you'll have to make the notes from the video.

[@gouravkumar9642]

Mam can i get your notes

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[@akashsinghdahiya5862]

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[@keerthim239]

Can you provide notes mam

[@krishchaudhary8371]

Where do you live ?

[@AnandSharma-lt8wq]

Mam can you upload your notes

[@rohansaraswat8873]

Sorry but you are just reading the notes, A bit of explanation would have been too helpful 😐

[@mazharul85]

Apu help me

[@testcase8070]

Thank you very much. Nice work. But please correct your pronunciation of "Gaussian". It was sounding a bit weird.

[@champu8835]

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[@anmol3]

The video is stuttering.

[@gayathriraghusing7686]

Your voice is tooooooooooooooo slow sis.. Not audible..

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time to buy new earphones

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[@SahilGupta-td7vu]

Anushree Ji can we get to know you more in person? like on Insta.

[@dicklexiclemon7487]

Hey whats the difference between weighted avg and gaussian? both had the same weights in your example.

[@ravikiran4495]

Just my dumb observation but I think Gaussian is probably more accurate, if you can see the matrix you kinda can observe two normal distributions along x&y axes of central pixel's(Target pixel) row and column the diagonal ones however, are having a very little weightage because of the way that they're too far from the centre most likely be less influenced by the value(Intensity even in minute levels) from the central pixel, the gaussian filter here takes variance into account while assigning such weights,Where the WA filter doesn't and ofcourse exponential being more smooth than a "linear" weighted average gives us more room to play with? But the end of the day its all an approximation which depends on several physical/Optical factors.so there's that.

[@mohamedessawey4192]

You're an amazing instructor. Simple & clear explanation, perfect understandable English, and straight to the point! Thank you for your effort.

[@jesus99384662]

You're an amazing instructor. Simple & clear explanation, perfect understandable English, and straight to the point! Thank you for your effort.