Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
권호 표지
DOI QR코드

DOI QR Code

A study on color image compression using downscaling method and subsampling method

다운스케일링 기법과 서브샘플링 기법을 활용한 컬러 이미지 압축에 관한 연구

  • Lee, Wan-Bum (Deptartment of Computer.Software Engineering, Wonkwang University)
  • 이완범 (원광대학교 컴퓨터.소프트웨어공학과)
  • Received : 2018.11.20
  • Accepted : 2019.02.01
  • Published : 2019.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

Most multimedia signals contain image data, so the problem of efficient processing and transmitting the image data is an important task of the information society. This paper proposes a compression algorithm that reduces the color bits according to importance using YUV color space among the various methods of compressing image data. 4: 2: 2 subsampling is the standard in the field of video. Using the color information and the characteristics of the human retina, YUV color data was reduced by 4: 2: 2 subsampling. The YUV images and RGB images can be interconverted using the transformation matrix. The image data was converted into color space by YUV, and the relatively low U and V bits were subjected to a downscaling operation. The data was then compressed through 4: 2: 2 subsampling. The performance of the proposed algorithm was compared and analyzed by a comparison with existing methods. As a result of the analysis, it was possible to compress the image without reducing the information of the low importance color element and without significant deterioration in the quality compared to the original.

멀티미디어 신호의 대부분은 이미지 데이터가 차지하고 있어 이미지 데이터를 효율적으로 처리하고 전송하는 문제가 정보화 사회의 중요 과제라 할 수 있다. 따라서 본 논문에서는 이미지 데이터를 압축하는 여러 방식 중에 YUV색 공간을 이용하여 중요도에 따라 색상 비트를 줄이는 압축 알고리즘을 제안한다. 4:2:2 서브샘플링은 영상 분야에서 표준으로 사용되고 있다. 색 정보와 사람의 망막이 가지는 특성을 이용하여 4:2:2 서브 샘플링으로 YUV의 색상 데이터를 줄였다. YUV 이미지와 RGB 이미지는 변환 행렬을 통해 서로의 색 영역으로 변환하여 사용할 수 있다. 이미지 데이터를 YUV로 색 공간으로 변환하여 상대적으로 낮은 U, V 비트를 다운 스케일작업을 수행 한 후 4:2:2 서브 샘플링을 통하여 데이터를 압축한다. 기존의 방식들과의 비교를 통하여 제안한 알고리즘의 성능을 비교하고 분석하였다. 분석한 결과 중요도가 낮은 색상 요소의 정보를 줄인 제안된 방식의 결과와 원본과 비교했을 때 품질의 큰 저하 없이 이미지를 압축 할 수 있었다.

Keywords

SHGSCZ_2019_v20n2_20_f0001.png 이미지

Fig. 1. YUV separated into individual components (a) Original (b) Y Component (c) U Component (d) V Component

SHGSCZ_2019_v20n2_20_f0002.png 이미지

Fig. 2. Image with less than 6 bits of color information

SHGSCZ_2019_v20n2_20_f0003.png 이미지

Fig. 3. Original and down scaled images (a) Original (b) Original Zoom (c) 8:6:6 Down Scale (d) 8:6:6 Down Scale Zoom

SHGSCZ_2019_v20n2_20_f0004.png 이미지

Fig. 4. Original and 4:2:2 Sub Sampling images (a) Original (b) Original Zoom (c) 4:2:2 Sub Sampling (d) 4:2:2 Sub Sampling Zoom

SHGSCZ_2019_v20n2_20_f0005.png 이미지

Fig. 5. Original and 6:4:4 down scaled images (a) Original (b) Original Zoom (c) 6:4:4 Down Scale (d) 6:4:4 Down Scale Zoom

SHGSCZ_2019_v20n2_20_f0006.png 이미지

Fig. 6. 4:2:2 and 4:2:2 down scaled images (a) 4:2:2 Sub Sampling (b) 4:2:2 Sub Sampling Zoom (c) 4:2:2 Down Scale (d) 4:2:2 Down Scale Zoom

SHGSCZ_2019_v20n2_20_f0007.png 이미지

Fig. 7. 6:4:4 down Scale and 4:2:2 images (a) 6:4:4 Down Scale (b) 6:4:4 Down Scale Zoom (c) 8:6:6 Y‘U’V‘422 (d) 8:6:6 Y’U‘V’422 Zoom

Table 1. 4:4:4 YUV and 4:2:2 YUV

SHGSCZ_2019_v20n2_20_t0001.png 이미지

Table 2. 8bit Color and 10bit Color

SHGSCZ_2019_v20n2_20_t0002.png 이미지

References

  1. R C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd Ed., Prentice Hall, 2002.
  2. J.-G. Ko, Y.-S. Bae, J.-Y. Park, and K. Park, "Technologies Trends in Image Big Data Analysis," Electronics and Telecommunications Trends, Vol. 29, No. 4, pp. 21-29, August 2014. http://m.ndsl.kr/index.do
  3. CORRY, Michael Kenneth. System and method for converting video data between the RGB and YUV color spaces. U.S. Patent No 5,784,050, 1998.
  4. HUANG, Si Jun. Method for MPEG-2 4: 2: 2 and 4: 2:0 chroma format conversion. U.S. Patent No 5,650,824, 1997.
  5. ECKART, Stefan; FOGG, Chad E. ISO-IEC MPEG-2 software video codec. In: IS&T/SPIE's Symposium on Electronic Imaging: Science & Technology. International Society for Optics and Photonics, p. 100-109, 1995.
  6. Daniela Stanescu, Mirce Stratulat, et al. Steganography in YUV color space. In: Robotic and Sensors Environments, 2007. ROSE 2007. International Workshop on. IEEE, p. 1-4, 2007. DOI : https://doi.org/10.1109/rose.2007.4373981
  7. SANTHI, V.; THANGAVELU, Dr Arunkumar. DWT-SVD combined full band robust watermarking technique for color images in YUV color space. International Journal of Computer Theory and Engineering, 1.4: 424-429, 2009. DOI : https://doi.org/10.7763/ijcte.2009.v1.68
  8. SHAO, HAN, Jia-wei. Inter- transformation between YUV and RGB. Journal of Changchun University, 4:016, 2004,
  9. Seok-Woo Jang, Gyungju Lee, Myunghee Jung "Effective Detection of Target Region Using a Machine Learning Algorithm", Journal of the Korea Academia-Industrial cooperation Society, Vol. 19, No. 5 pp. 697-704, 2018. http://www.jkais99.org/journal/html/19_05.html