 Hello everyone. My name is Mr. Sandesh Pare. I am currently working as an assistant professor in the department of computer science and engineering at Vachan Institute of Technology Swadapur. In this video session, I am mainly going to cover the two topics which are run length encoding and the compression of the image. The techniques used for the compression of the image and the detailed algorithm means we have to understood the algorithm regarding the image compression. So, what will be the outcome of this video session? So, let us focus on that once at the end of this session you will be able to explain the size of the images is reduced using the compression techniques like run length encoding algorithm means how particular image will be reduced and how the optimal memory is used for to store the particular image you can able to explain to this. So, let us start with the topic that is run length encoding as the name itself suggests it is about the encoding of the run length. So, what is the run length? See, basic task is to compress the image. It means what we have to reduce the memory which is required for the storing of the particular image means we should not decrease the quality of the image we should not hamper the quality of the image but we have to reduce the size which is required to store the particular image. So, how we can do that using this run length encoding? So, what is run length encoding? It takes the advantage of the image coherence. Now, what is the image coherence? Okay, image coherence means what in the particular image there are multiple pixels on the image. Otherwise, we can say that a particular area in the image which is holding the same color. Okay, it means it is holding the same properties it is holding the same characteristics of the pixels means all the pixels in that particular area which is of the same image means within that area are holding the same values means for every pixel the values will be same in that particular area of the image. So, it is called as the image coherence. So, it is nothing but it specifies a number of successive pixels with the same entity. It means what instead of storing every pixel value independently we can store the value and the number of adjacent pixels which are holding that value understood means the particular value and the number of successive pixels which are holding the same value it will be described. So, this information is sufficient to describe about the image. Okay, so you can see the format of the encoded data the first column is the intensity and the number of pixels which are holding the same intensity it is number is defined by the run length. So, as you can see the image in that you can see the yellow part is there. Okay, it is used to show particular image on the screen. Okay, so how we can store the image in this format just we have to store the starting and ending index of the particular pixel in that particular scan line. Okay, as you can see on the right side for the row one. Okay, there is only one pixel which is of the yellow color it means we have to display that only one pixel. So, only one value is hold at there instead of storing each and every value of the pixel in that scan line we can store just a pixel which we need to show it on the screen or which we need to on on the screen. Okay, but it may be in the range as we can see go to the row number two there are two pixels which are holding the again same characteristics at the time the starting and ending index of that pixels which starting index and the ending index of the particular scan line which are on in position which are to display of the color. Okay, here we are talking about the monochromatic display okay we are displaying the only color it means the image of the black and white part okay only two colors are there. So, we have to store only the one value that is it is on or off by default it is off. Okay, so by using the starting and ending index of the particular scan line we can show that which pixel should be marked as on and which pixel should be marked as off. Okay, so now we have seen monochromatic display now we will talk about the color display okay in monochromatic display we have to just store what whether particular pixel is on or off we have to store index values of the starting index and ending and according to that we have to display a particular image but what about the color display in the color display the pixel is on but of the different color understood means we have to display particular pixels on the screen on the scan line but they may hold different colors isn't it. So, we have to differentiate between the monochromatic and color display. So, what happens the ideal compression of run length encoding should be less than one okay means after compression the size must be reduced okay the ratio between the non compressed image to the compressed one should be less than one it means the size should be reduced after the compression otherwise that run length encoding will not be considered as the correct one and size of the memory which is required to display that particular image okay. So, as we see the compression technique in the previous diagram okay for one pixel it is holding only one value and one certain ranges are there then for every range on the scan line we have to store the two indexes starting an index ending index okay. So, according to the frames different frames and the different images on that frame the size of the memory which is required to store that image it may be vary. So, format of the encoded data in the color display is in this manner run length means the number of successive pixels which are holding the same characteristics and after that the RGB values okay it means red intensity green intensity and the blue intensity. So, it is the combination of the RGB values and that combination is used for the number of adjacent pixels we have to store that. So, using this RGB values there are number of colors are there which denotes this means for zero value of the RGB it means the black one and certain ranges are there one zero zero is for red zero one zero for green zero zero one for blue okay one one zero for yellow zero one one for can one zero one for mangata and triple one means white. So, in this format the different particular images the values of the colors are used in this three-bit platform. So, problem statement what is the in most of the images there is bulk of the portion which is having the same color that is all pixels residing in the region holding the same value of the color. So, it is waste of memory to store this same value of the color for all the pixels residing in that particular region. So, by minimizing the storage of this type we can compress the particular image one question is there for guys that what can be limitations of the run length encoding method and in image compression technique. So, there are some situations means where we does not contain any bulk data where all pixels hold the same color at that time the efficiency of the run length MN code method decreases because what happens the particular image is containing successive number of on and off bit are there suppose okay then for that particular situation the as I said earlier that for the particular value we have to store the starting index and ending index value okay but if suppose there is one pixel on and one pixel off and this pattern is going on successively. So, for every pixel we have to store two values. So, efficiency is decreased by 50 percentage here okay means instead of storing one value of the pixel color for one index you have to store two values as a range of the index. So, it should not be happen. So, it is the drawback of this run length encoding technique. So, as I said earlier it is the one image you have to see this okay there is a lining black and white color linings are there okay one pixel is black one pixel is white again one pixel is black and white okay. So, as you can see on the right side okay there are 15 number of pairs are there okay which are holding these four bits means one one means the black one and next run length is one and again zero means white and the run length is one. So, for every pixel we have to store the two values here. So, it should not be happen if then compression is not considered as the efficiency in this case at least because the normal image if you stored in the memory then the frame will contain only one pixels one value either it is one or zero okay. So, what happen the non compressed image is holding the half size but the compressed image will contain the double size. So, it should not be happen. So, in this case efficiency is decreased by 50 percentage. So, in this manner the encoding will happen as you can see eight a bits are there then five a bits and lastly two c bits are there. So, it is compressed a is holding say eight value b is five and c is two. So, these are some references I use to make this video. Thank you.