Keyword:RLE (run length encoding), image compression, R (Red), G (Green ), B(blue).

Transcription

1 The Run Length Encoding for RGB Images Pratishtha Gupta 1, Varsha Bansal 2 Computer Science, Banasthali University, Jaipur, Rajasthan, India 1 Computer Science, Banasthali University, Jaipur, Rajasthan, India 2 Abstract: This document presents the basically the implementation of Run Length Encoding that is one of the lossless image compression technique. This paper gives the implementation of Run length encoding compression algorithm which is capably well-matched for RGB images data. Here considered painted and natural images for the examination of implemented scheme. By this technique image can be compressed and occupy short space in memory, and improve the performance and result of the system. There for that RUN LENGTH ENCODING split big sequences of runs that totally affects compression ratio into small sequences of runs without degrading the quality of image. Keyword:RLE (run length encoding), image compression, R (Red), G (Green ), B(blue). Introduction of Image Compression Image compression and processing is currently a well-known context for computer science countryside. Essentially, image compression is the processes of images that change the images into small codeword without any loss of important information. The image compression process provides the most favorable for consumption for storage, Nagarajan A. et al, [2]. The less size of images allows more images to be stored in a less memory space or disk drive. It also uses short time slot for images to be sent over the network or downloaded from web pages. Gupta G. et al [1].In other words, the basic enthusiasm of image compression is using short amount of data to represent the innovative image without compromising with information. And reduce the size of image for decrease the transmission time. Introduction of Run length encoding RLE (Run-length encoding) is a very popular,simple and easy concept of data compression, in which the count of rate of same data is stored as a single data value and single count. This is most useful for the images that contains many such runs, huge number of same data value : for example, a simple RGB image such as same color occur many time. It is less helpful with RGB images that don't have many runs or same value data as it could to a great extent increase the files size The Run length encoding technique performs a lossless compression of input images that is based on sequences of identical values (runs), Amin A.,et al. [4] Basic Working of Run Length Encoding Here, let s take the example of image and perform the run length encoding. There will be too much long runs of white pixels, and short runs of black pixels. Here considered take a single scan line or row of image with B representing a black pixel and W representing white pixel. AAAAAAAAAAABAAAAAAAAAAAABBBAAAAAAAA AAAAAAAAAAAAAAAABAAAAAAAAAAAAAA Here apply the run-length encoding for image compression algorithm to the above scan line, we get the following: (12A) (1B) (12A) (3B) (24A) (1B) (14A). 12 A, means 12 count of white color pixel, (3B) 3 means count of black color pixel and so on. Run Length Encoding Scheme The basic scheme of run length encoding is to improve the system working and performance. This technique helps to decrease the memory that is obtain by Images. Run Length Encoding technique and helps to increase the compression velocity This paper planned some alteration in RLE scheme; this modification provides major improvement in compression velocity of image data. First of all, analyzing the inputting RGB image at the first step of algorithm. If there are any large sequences of equivalent intensity or pixel value, that may require the big number of bit for represent the length of each run. In proposed method if pixel of input image contains same or nearest value with its adjacent pixel then both pixel values consider as a same data or intensity value in RGB image, Joseph S., at al.[5] Proposed Methodology The basic viewpoint behindhand the selecting Run Length Encoding (RLE) technique, that is loss less technique and based on inherent property of images data and they have same patterns in nearest pixel area of image. Specifically the intensity of two pixels is very much same in nearest area. This belongings of image is exploited to design a very effective image compression technique. The technique basically used in this compression area and Run Length Encoding (RLE) are described in this segment of document. Here consider Run Length compression for given image. The bellow image has 1

2 RGB color combination. Image read from first pixel of image and starts compression. fig 1. RGB image with pixel value. Here each cell of matrix represents the pixel. This algorithm scans image one row at a time. This technique shows result as above manner. For example the result is shows as a, 2R 2G 3B that is represents 2R means 2 pixels of red color. 2G means 2 pixels of green color. 3B means 3pixels of blue color. And so on. The basic steps of proposed algorithm of Run Length Encoding are as follow Step 3: Step 4: Step 5: For reconstructing compressed image, a. Construct the i th row of compressed image with putting run length value in reconstruct array from compressed array. b. Then construct i+1 th row then next row and so on. Step 3 is repeated until reconstruct array fill by value of compressed array. Reconstruct array, store as a decompressed image file. Compression Step 1: Firstly, Input the colored source image file. Step 6: Display the decompressed image file. Step 2: statement Find out the size of source image by following [row,col,dim]=size(i); Step 3: Read pixel values from first pixel of source image by help of this statement X=impixel (I,i,j); Here i=row; J= columns; I= Image; Step 4: Step 5: Step 6:. Step 7: Read next pixel value, if current pixel is end of the image then exit from loop otherwise (i).if next pixel value is same from previous than Count = count+1; (ii). Else if mismatch in value of next pixel as the previous than save as the new value of pixel in array. Read and count all the value of pixel. Go to step 4 until all pixel read Display the result array with intensity value. Test Result Input: This function takes source colored images. Output: This function provides the compressed image file. Decompression Step 1: Firstly Read compressed array which store the intensity value and attain the image size. Step 2: Generate the vacant array for reconstruction of compressed image. New array ( :, :,1:3); Figure 2. bag.jpg Before compression of Bag.jpg image 2

3 Size row =235 Col = 300 = bits /8 = bytes After compression of above image Compression percentage is 82.5% Before compression for Thumbnail.jpg image Size row = 699 Col = 697 = bits /8 = bytes After compression of above image Compression percentage is 20.29% Examination of Run Length Encoding Technique for Colored Image Name Row (i) Col (j) RGB bits Total size before compression Bag.jpg *3= bits Thumbnail *3= jpg bits Size in bytes bytes bytes According to result of Run Length Encoding scheme, This technique of compression works efficiently where large areas of similar pixel value takes place in image data. In the image data Bag.jpg, RLE compression technique shows much more compression percentage that is 82.5% because here is large number of pixels have same value in it. Now, consider the Thumbnail.jpg image, this image slightly compressed than Bag.jpg image data because there are many colors present in Array size in row Array size in col Compression calculation / * / *100 Compression Percentages. 82.5% 20.29% Table 1. This table contains the result of run length encoding scheme. it. Conclusion This Document provide a working of Run Length Encoding compression technique (RLE) of RGB images data. It is the unambiguous from of algorithm that remove the pixel value from image data. Compression is very much useful and important part of Image Processing filed. Fundamentally these methodology will discover complete use in Medical image, GIS images (geographical information system), because these type of image has large area of identical pixel pattern. Figure 3. Thumbnail References [1] Nagarajan A., Alagarsamy K. AN ENHANCED APPROCH IN RUN LENGTH ENCODING SCHEME International Journal of Engineering Trends and Technology- July to Aug Issue 2011 [2] Gupta G., Gupta K.L. Jyoti A., AN ADVANCED COMPRESSION APPROACH WITH RLE FOR IMAGE 3

4 COMPRESSION International Journal of Advanced Research in Computer Science and Software Engineering Volume 4, Issue 2, February 2014 [3] Akhtarl M.B., Qureshi A.M., and Islam Q., OPTIMIZED RUN LENGTH CODING FOR JPGE IMAGE COMPRESSION USED IN SPEC RESEARCH PROGRAM OF IST.( /11/$ IEEE) [4] Amin A., Aheman Q.,Junaid M. Habib M.Y, Anjum W., MODIFIED RUN LENGTH ENCODING SCHEME WITH INTRODUCTION OF BIT STUFFING FOR EFFICIENT DATA COMPRESSION 6 th International conference on internet technology and secured transaction December 2011 Abu Dhabi 2011 IEEE) [5] Joseph S., Srikanth N. A NOVEL APPROCH OF MODIFIED RUN LENGTH ENCODING SCHEME FOR HIGH SPEED DATA COMMUNICATION APPLICATION International Journal of Science and Research (IJSR) Volume 2 Issue 12, December

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