convolution of images

[@e3a87]

"I hope this helps man!!" goes directly into my lazy soul hwo never studies until the night of the exam! Thanks dude, it helps a lot

[@someoneelse707]

Same😂

[@emirhandemir3872]

Dude! We gotta do something about it. You probably graduated or dropped school but I at least need to quit this stupid habit of mine!

[@e3a87]

@@emirhandemir3872 ​ Bro, no one can destroy iron but its own rust !! I don't know what is your goal and what are you going through but you need to realize one thing: You are the only one that can make this work and you are the only one that can f*ck it up You either control your mind or it controls you, you gotta choose... But yeah I graduated thinking that the struggle will end with the degree but guess what... it never ends! This phenomenon of laziness is a perpetual war. I hope this helps man!!

[@wolfabod9715]

@@e3a87 my exam is in 8 hours i really hope it does !!

[@XXxlightmarex]

3:51 "one second, let me just do a cheeky line of coke real quick"

[@triton62674]

Haha!

[@feelsunbreeze]

LMAOOOO

[@riseabovehate9476]

For convolution, you flip the mask horizontally as well as vertically and then computer the SOP. Since the mask, you have taken is symmetric Correlation and Convolution happen to be the same

[@tallurinani6059]

Bro, you are a savior. Thank you sooooo much. i didn't understand when i tried it fomr many websites and yt videos, yours just went straightly into the brain.. Thank you

[@youtubegiuhotoinhe]

2024 and you are saving me sir! Thank you very much

[@etziowingeler3173]

I like your laid back style Duderino, and it really helps

[@ancient_living]

Great work explaining that the size of the convolved image is decreased in dimensions. Keep up the good work.

[@brimamedou]

Wow, dude! That was a great explanation. I precisely understood the details of this process. I will apply that to all sorts of areas in my life. You rock, Dãmáiou!

[@DumplingWarrior]

I like the fact that I'm actually learning something while laughing lol, great video! you're funny

[@tempdrive2342]

it was very useful put more videos

[@kuqiu5003]

Very clear interpretation. Thanks a million!

[@hieutran5099]

Thank you for the very clear and precise answer.

[@rahulkambale2627]

Great

[@tymothylim6550]

Thank you very much for this video, Alexandre! It was a really simple and easy-to-understand video :)

[@ifargantech]

This video is means alot to me. Thank you! Please make more videos on DIP

[@highelojungler]

lmao all these videos all professional and ur calling me dude and man, love you. take this like

[@alihan60]

Clear explanation! This is what i need! Thanks man you save the day!

[@AzarZeynalli-mp5zj]

It helps more than you imagine. Thanks man:)

[@navigator171]

Finally somebody that did exactly what I need... Thanks man.

[@navigator171]

Você deveria fazer mais videos como esse, salvaria outras vidas.

[@alexmaingi9327]

Precise and understandable, Good job!!

[@gravinpatel7700]

Thank you for giving such a simple example and explanation

[@osamamirza4220]

Thanks man!! this helped me a lot

[@vagumanasa7044]

Literally this helped me a lott...thnq soo soo muchhh...

[@Isa25monalisa]

THANK YOU!!! You helped me SO MUCH!!! Such an excellent explanation!

[@wqkkta8787]

This helped me so much! Thank you!!!

[@adl30]

You saved me from reading big book of convolution theory. Respect bro.

[@StrangeParticl]

Thank you for the simple explanation of the convolution process. You did like it is a simple adding number to each other ... That is grat, Sir. Thank you so much agine

[@Megan-gl7pi]

Thanks for explaining this super simply and quickly.

[@zephjaz947]

Thank you for the precise explanation

[@minhanhpham2508]

You save me in my midterm exam, thanks a lot!

[@glebignites5278]

Great explanation! Thank you very much.

[@EnglishRain]

This is so excellent thank you so so much

[@avaneeshchavan8821]

Thanks, man i wasn't able to understand this in my school and now I understood it in 5 mins

[@ghufrongalih8354]

really help me man, thx have a good day always

[@ilegadh]

Thanks, this really helped me understanding!

[@SirJonathonDanielGregorySrVthe]

You have no idea how fucking dull my lecturer is for this unit, this has helped a lot in avoiding something that probably would've been a half-hour explanation.

[@meirzilkha]

Thanks! This is great.

[@ajanthaalakkshmanan5854]

Awesome explanation

[@eyadbereh]

Bro, I'm having this for an exam tomorrow, and you just saved me from an M x N headache

[@freedom1880]

Thank you.I am deeply thankful.

[@ashutoshmaurya9726]

Thanks for such a nice explanation .

[@fase29]

thank you very much!

[@AR-scorp]

Helped a lot. Thank you.

[@karthikrajaloganathan3067]

Useful . Do some more videos

[@tawheedalabed6447]

many thanks realy it is very good

[@jcgonzalez9122]

dude this was awesome lol.

[@philipp849]

I cannot thank you enough. You saved my butt.

[@user-dg4oo8tn3w]

Good job man!!! It's useful.

[@OmarAhmed-tk1ow]

Great explanation

[@drchastr208]

great video man

[@ajinzrathod]

I was laughing at 3:56. Really appreciate your efforts. Thanks

[@danusd1811]

Thanks a lot bro

[@Arnankhan]

Thank you! Very good tutorial.

[@narendrakumar5504]

Clear and concise explanation

[@MattoUchiha]

Thank you so much this made it seem so simple lol

[@chvrleshd]

please how do you convolve and wrap around image cyclically??!

[@kwekureginaldwade]

Great explanation !!!

[@kavishkanilan9137]

😍

[@abdelhafidbenchikh4426]

Very useful, thanks so much

[@JoeDhirk]

Thank you.

[@saifulahmad3770]

very helpful. Thank you

[@jyothish99]

Great explanation dude !!

[@syedmhamudulhasanakash1675]

Best explanation ever man!

[@farhamrezqimaarifm8537]

thanks dude its help a lot

[@Sean-ow7qb]

amazing!

[@abhijithbs997]

cool stuff dude..... Thanks a lot

[@pawanyendigeri3157]

Nice video

[@metinyorgun1963]

You should scale pixel value because its cannot be greater than 255.

[@imagenigraphics]

Question: After applying convolution, is the resolution of the image reduced or maintained? If maintained, how when it looks like it was reduced?

[@user-ok3qx5kf4o]

Thank you🌸

[@shwetabhsingh5437]

for sure bro, thanks

[@ashvinisharma8178]

Thank You dude

[@RaunakPinakJoshi]

Thanks man! Really helpful.

[@Agreedtodisagree]

Thanks.

[@juyeon_kim]

i think its correlation but thank you a lot. you helped me understand

[@gaoqiangzhou9960]

life saver!

[@zhiyiwang6466]

still deserves an upvote

[@MrRobi10]

Hello, I have an 11×11 image having in its center a 5×5 square, the image it's noiseless and I don't know how to compute the gradient of the image function given by the compass operator for this image. If I remember correctly, I should use a derivative, but I don't know exactly what and how can I use it. Can you please help me?

[@waytoprogramming]

Well done.

[@chanhungnguyen3089]

I saw in many documents they say the multiplication between the kernel and each patch of the image matrix is a dot product. Can you explain it?

[@arash4232]

Hi, So what? Should we normalise the calculated values? What colour does 514 refers to?

[@AhmadImtiaz320]

For larger image, do we have to stick to 3x3 mask ? Or the mask increases with the size of image?

[@marcelmcjackson4257]

You don't have to stick to a 3x3 mask. It can be whatever size

[@AhmadImtiaz320]

@@marcelmcjackson4257 but the result will be different each time . Right?

[@marcelmcjackson4257]

@@AhmadImtiaz320 It will be different when using other masks. The convoluted matrix will be smaller when using a 5x5 mask. And the result of course depends on the numbers used in the mask^^

[@AhmadImtiaz320]

@@marcelmcjackson4257 Thank you :)

[@renasouza8261]

Very good vídeo mano

[@alkodjdjd]

Ajudou muito a pesar de ter ficado zonzo de tanto a camera se mexer :)

[@aswinsurendrank6560]

this looks easy: those who know the real one💀

[@I34R]

how do you do it with circular indexing?

[@arturkot4108]

Thanks, man!

[@shoruqm9753]

You saved my life man

[@imranwahid9871]

Thanks a lot brother. It helped.

[@crazyvideos6474]

Great explanation but I think you are wrong. You are doing a correlation not a convolution

[@alexandredamiao1365]

Hi, thank you for the polite criticism. However, the operations I gave in the video are indeed used in convolution of images. Take a look at the explanations given in these links: web.pdx.edu/~jduh/courses/Archive/geog481w07/Students/Ludwig_ImageConvolution.pdf, machinelearninguru.com/computer_vision/basics/convolution/image_convolution_1.html, docs.gimp.org/en/plug-in-convmatrix.html

[@turbasdd]

Well, the thing is that this kernel you used as example is symmetric, because of that when you flip it horizontally and vertically (before the convolution) you get the exactly same kernel... Therefore, the way it is explained it works, but because the kernel is symmetric... and then it seems like a correlation as the other fellow mentioned. You can see this in here machinelearninguru.com/computer_vision/basics/convolution/image_convolution_1.html And you can also read about on chapter 3 of the book: "Digital Image Processing" by Rafael C. Gonzalez and Richard E. Woods (www.amazon.com/Digital-Image-Processing-Rafael-Gonzalez/dp/0133356728)

[@ashavarghese8458]

Thanks

[@juaneugeniodebenedettti6187]

@@turbasdd touche

[@rionacko748]

@@turbasdd That link no longer working :(

[@mattkan2876]

Sir, your tutorial is nice in contents, but its better for you to buy a fixed frame to hold your mobile phone recorder

[@stavrosk.3773]

thanks DUDE

[@manjukarthik9598]

I think what you have shown is incorrect, coz using the sliding window concept you would calculate the value of the pixel that corresponds to the middle value ( say in a 3 X 3 kernel the value at 1,1)of your kernel and not the first value as explained. Also you need to divide it by the total (sum) of your kernel values(in your case its 4 that is 649/4 giving you the value 162.25 for the value in the original image at 32).

[@BrandonLobo]

Thanks. I'm not looking at images, but still needed convolution and I had a feeling it needed to be dived by some value, else it makes no sense.

[@ubaidurrehman4377]

great, there was a mistake

[@vloggetts]

I agree that he should have replaced the middle value but I think dividing by the kernel sum is only for a weighted arithmetic mean filter whereas this is just a genera; convolution

[@JimmyJohnston3rd]

I will confirm that yes you are correct. The resulting value is the middle. For a 3x3 kernel like this we would add a top row, bottom row, initial column and last column of 0's to address the borders of an image or just ignore the borders all together. The end result should be a matrix of the same size for image processing at least.

[@mohammadalifffirdausmohamm8125]

i love this video very good

[@notben49]

why are you black

[@markpx]

Since the convolution result produces numbers higher than 255, it no longer can be treated like an image?

[@Serinebey13]

Thank you bro

[@ann61320]

terrible camerawork but solid explanation xD thanks bro!

[@DangThinh261]

Omgg thanx

[@cimodd3031]

I love you man

[@muneebabbas2424]

I'm working on an example similar to this, when using the kernal on the image matrix I got an output of -2 (some of the values in the kernal were negative), I'm not sure if you can get a negative value for the output but what would that mean for the image matrix if, when convoluted, a pixel becomes a negative value?

[@fiethsing9988]

For those wondering, when you get a negative value, you just put the lowest value the pixel can be. So if you got a greyscale image and it's pixel values range from 0-255, you'd put 0.

[@maheshbhosale1838]

this is not what convolution is, you need to flip the kernel first. This is a correlation.