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![ Sugreev Kaur et al. [4] presented a high speed and area efficient DWT processor based design for Image Compression applications. Nikolay Ponomarenko et al. [7] proposed DCT based image compression using blocks of size 32x32 is considered. Zhigang Gao et al. [6] presented a quality constrained compression algorithm based on DWT is proposed. Maneesha Guptaam et al. [9] develop some simple functions to compute the DCT and to compress images. Sunday, October 15, 2023 9](https://image.slidesharecdn.com/mynitinmtechdissertation-231015100540-face4704/75/MTech-Dissertation-ppt-9-2048.jpg)
![ [1] Liu Chien-Chih, Hang Hsueh-Ming, "Acceleration and Implementation of JPEG 2000 Encoder on TI DSP platform" Image Processing, 2007. ICIP 2007. IEEE International Conference on, Vo1. 3, pp. III-329-339, 2005 [2] H. S. Malvar, “Fast progressive image coding withoutwavelets,” in Proc. 2000 Data Compression Conf., Mar. 2000, pp. 243–252 . [3] Anna Saro Vijendran, Vidhya.B" A Hybrid Image Compression Technique Using Wavelet Transformation - MFOCPN and Interpolation"Global Journal of Computer Science and Technology Volume 11 Issue Version 1.0 March 2011 [4] Sugreev Kaur and Rajesh Mehra, “HIGH SPEED AND AREA EFFICIENT 2D DWTPR OCESSOR BASED IMAGE COMPRESSION Signal & Image Processing : An International Journal(SIPIJ) Vol.1, No.2, December 2010. [5] Kamrul Hasan Talukder and Koichi Harada, “Discrete Wavelet Transform for Image Compression and A Model of Parallel Image Compression Scheme for Formal Verification”, , Proceedings of the World Congress on Engineering 2007 Vol I WCE 2007, July 2 - 4, 2007, London, U.K.](https://image.slidesharecdn.com/mynitinmtechdissertation-231015100540-face4704/75/MTech-Dissertation-ppt-17-2048.jpg)
![ [6] Zhigang Gao, Yuan F. Zheng, “ Quality Constrained Compression Using DWT Based Image Quality Metric”, Dept. of Electrical and Computer Engineering The Ohio State University [7] Nikolay Ponomarenko ,Vladimir Lukin, Karen Egiazarian, Jaakko Astola. “DCT Based High Quality Image Compression”. IEEE Trans. Image Proc, vol. 11, pp. 1688–1693 [8]M. Mozammel Hoque Chowdhury and Amina Khatun," Image Compression Using Discrete Wavelet Transform",IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 1, July 2012 [9]Maneesha Guptaan and Dr.Amit Kumar Garg,"Analysis Of Image Compression Algorithm Using DCT",International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue 1, Jan- Feb 2012,pp.515-521.](https://image.slidesharecdn.com/mynitinmtechdissertation-231015100540-face4704/75/MTech-Dissertation-ppt-18-2048.jpg)
![ [10] Yamanaka, O.; Yamaguchi, T.; Maeda, J.; Suzuki, Y.; “Image compression using wavelet transform and vector quantization with variable block size”, IEEE Conference on Soft Computing in Industrial Applications (SMCia), 2008, Page: 359 – 364. [11]Maneesha Guptaan and Dr.Amit Kumar Garg,"Analysis Of Image Compression Algorithm Using DCT",International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue 1, Jan- Feb 2012,pp.515-521. [12] Syed Ali Khayam, "The Discrete Cosine Transform (DCT): Theory and Application" Department of Electrical & Computer Engineering,Michigan State University ,March 10th 2003.](https://image.slidesharecdn.com/mynitinmtechdissertation-231015100540-face4704/75/MTech-Dissertation-ppt-19-2048.jpg)
MTech Dissertation.ppt
- 1. Sunday, October 15,2023 1
- 2. Introduction ofDigital Image Image Compression Image File Format Application of Image Compression Sampling & Quantization Literature Survey Problem Statement Transformation Algorithm Result Analysis Function Parameter Conclusion and Future Work Publications References Sunday, October 15, 2023 2
- 3. It iselectronic representation of image. A image contain the number of pixels. Each pixel contain the information about the colour or intensity. All pixel are arranged in Grid Format. The number of pixels-per-inch (PPI) is a good indicator of the resolution. Greyscale images are normally displayed in 8-bit manner In digital imaging 24-bit mode which represent true colour. Sunday, October 15, 2023 3
- 4. Reducing thesize Encoding information more efficiently. Easy and fast Transmission. Eliminate space character Eliminate duplicate character Lossless & Lossy Compression. Run Length Encoding Lossless compression JPEG compression Sunday, October 15, 2023 4
- 5. It isvery easy to implement. It provide a quick method of compression data. Example: Message for the compression: AAAABBBAABBBBBCCCCCCCCDABCBAAABBBBCCCD is replaced by 4A3BAA5B8CDABCB3A4B3CD Sunday, October 15, 2023 5
- 6. JPEG (JointPhotographic Experts Group). GIF (Graphics Interchange Format). BMP (Bitmap). PNG (Portable Network Graphics). TIFF (Tagged Image File Format). PSD (Adobe Photoshop Document). WEBP Sunday, October 15, 2023 6
- 7. High DefinitionTV. Satellite remote sensing. Fax Transmission. Health business for storage of medical images. Passport Department. Driving License Department. Election Commission Department. Web Application. Sunday, October 15, 2023 7
- 8. Digitizing thecoordinate values is called sampling. Digitizing the amplitude values is called quantization. Sunday, October 15, 2023 8
- 9. Sugreev Kauret al. [4] presented a high speed and area efficient DWT processor based design for Image Compression applications. Nikolay Ponomarenko et al. [7] proposed DCT based image compression using blocks of size 32x32 is considered. Zhigang Gao et al. [6] presented a quality constrained compression algorithm based on DWT is proposed. Maneesha Guptaam et al. [9] develop some simple functions to compute the DCT and to compress images. Sunday, October 15, 2023 9
- 10. Why thereare so many algorithms and methods for storing and transferring images in a compressed form. We have done work into the principles of images and its related areas including compression and decompression, image displaying and some advanced techniques used to enhance compression ratios. Sunday, October 15, 2023 10
- 11. The DiscreteCosine Transformation (DCT) is expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. Figure 1 :DCT of an image Sunday, October 15, 2023 11
- 12. The DiscreteWavelet Transform (DWT), which is based on sub-band coding, is found to give up a fast computation of Wavelet Transform. DWT is easy to execute and reduces the computation time and resources mandatory. Figure 2 : Transformation based compression Sunday, October 15, 2023 12
- 13. Sunday, October 15,2023 13 Figure 3 : First & Second level wavelets decomposition
- 14. Compressed Algorithms: Step1:Take the input image (e.g 5.bmp). Step2: using wavelets transformation decomposition at second level (db6.db7,db8) Step 3: Find out the block 8x8 after step 2and applied cosine transformation for each block. Step4: apply quantization and sampling process for each block. Step5: Save the compressed image into 5_com.NIT Sunday, October 15, 2023 14
- 15. Decompressed Algorithms: Step 1: read the compressed image (5_com.NIT) Step2: Apply de sampling and de quantization for each block. Step 3: apply inverse cosine transformation. Step 4: then combined the block and apply inverse wavelets transformation. Step 5: Save the decompressed image into 5_dcom.bmp Sunday, October 15, 2023 15
- 16. Figure 4 :Image Compression tool Sunday, October 15, 2023 16
- 17. [1] LiuChien-Chih, Hang Hsueh-Ming, "Acceleration and Implementation of JPEG 2000 Encoder on TI DSP platform" Image Processing, 2007. ICIP 2007. IEEE International Conference on, Vo1. 3, pp. III-329-339, 2005 [2] H. S. Malvar, “Fast progressive image coding withoutwavelets,” in Proc. 2000 Data Compression Conf., Mar. 2000, pp. 243–252 . [3] Anna Saro Vijendran, Vidhya.B" A Hybrid Image Compression Technique Using Wavelet Transformation - MFOCPN and Interpolation"Global Journal of Computer Science and Technology Volume 11 Issue Version 1.0 March 2011 [4] Sugreev Kaur and Rajesh Mehra, “HIGH SPEED AND AREA EFFICIENT 2D DWTPR OCESSOR BASED IMAGE COMPRESSION Signal & Image Processing : An International Journal(SIPIJ) Vol.1, No.2, December 2010. [5] Kamrul Hasan Talukder and Koichi Harada, “Discrete Wavelet Transform for Image Compression and A Model of Parallel Image Compression Scheme for Formal Verification”, , Proceedings of the World Congress on Engineering 2007 Vol I WCE 2007, July 2 - 4, 2007, London, U.K.
- 18. [6] ZhigangGao, Yuan F. Zheng, “ Quality Constrained Compression Using DWT Based Image Quality Metric”, Dept. of Electrical and Computer Engineering The Ohio State University [7] Nikolay Ponomarenko ,Vladimir Lukin, Karen Egiazarian, Jaakko Astola. “DCT Based High Quality Image Compression”. IEEE Trans. Image Proc, vol. 11, pp. 1688–1693 [8]M. Mozammel Hoque Chowdhury and Amina Khatun," Image Compression Using Discrete Wavelet Transform",IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 1, July 2012 [9]Maneesha Guptaan and Dr.Amit Kumar Garg,"Analysis Of Image Compression Algorithm Using DCT",International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue 1, Jan- Feb 2012,pp.515-521.
- 19. [10] Yamanaka,O.; Yamaguchi, T.; Maeda, J.; Suzuki, Y.; “Image compression using wavelet transform and vector quantization with variable block size”, IEEE Conference on Soft Computing in Industrial Applications (SMCia), 2008, Page: 359 – 364. [11]Maneesha Guptaan and Dr.Amit Kumar Garg,"Analysis Of Image Compression Algorithm Using DCT",International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue 1, Jan- Feb 2012,pp.515-521. [12] Syed Ali Khayam, "The Discrete Cosine Transform (DCT): Theory and Application" Department of Electrical & Computer Engineering,Michigan State University ,March 10th 2003.
- 20. THANK YOU Sunday, October15, 2023 20