Conference Paper

Reversible integer color transform with bit-constraint

Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
DOI: 10.1109/ICIP.2005.1530554 Conference: Image Processing, 2005. ICIP 2005. IEEE International Conference on, Volume: 3
Source: IEEE Xplore

ABSTRACT In color image processing, the RGB color coordinate is usually transformed into another one (e.g., YIQ or KLA) for system fitting or other purposes. Most of the color transforms are done by 3×3 matrices. However, these matrices are always not fixed-point. In this paper, we use a systematic algorithm to convert every 3×3 color transform into a reversible integer-to-integer transform. The resulted transform can be implemented with only fixed-point processor and no floating-point processor is required. Moreover, with the use of ladder-truncation technique, we can make least bit of the output the same as that of the input, and the long bit-length problem that always occurs for other integer transforms can be avoided. We derive the integer color transforms of RGB-to-KLA, IV1V2, YCrCb, DCT, and YIQ successfully.

Download full-text

Full-text

Available from: Jian-Jiun Ding, Aug 30, 2015
0 Followers
 · 
323 Views
  • Source
    • "(a) illustrates an existing approach reported in [9] [10]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In this report, permutation of order and sign of signals are introduced to avoid singular point problem of a reversible transform. When a transform is implemented in the lifting structure, it can be "reversible" in spite of rounding operations inside the transform. Therefore it has been applied to lossless coding of digital signals. However some coefficient values of the transform have singular points (SP). Around the SP, rounding errors are magnified to huge amount and the coding efficiency is decreased. In this report, we analyze the SP of a three point KLT for RGB color components of an image signal, and introduce permutation of order and sign of signals to avoid the SP problem. It was experimentally confirmed that the proposed method improved PSNR by approximately 15 [dB] comparing to the worst case.
    Proceedings fo the Picture Coding Symposium, PCS 2010, Nagoya, Japan, 8-10 December, 2010; 01/2010
  • Source
    • "Unfortunately, the conversion from the RGB color space to YCbCr coordinates (or other coordinates ensuring band decorrelation) is an affine operation with non-integer coefficients, hence compromising the lossless nature of the scheme. To avoid this problem we used a reversible integer approximation of the correct transform in a way similar to that described in [8]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The feasibility of lossless compression of encrypted images has been recently demonstrated by relying on the analogy with source coding with side information at the decoder. However previous works only addressed the compression of bilevel images, namely sparse black and white images, with asymmetric probabilities of black and white pixels. In this paper we investigate the possibility of compressing en-crypted grey level and color images, by decomposing them into bit-planes. A few approaches to exploit the spatial and cross-plane correlation among pixels are discussed, as well as the possibility of exploiting the correlation between color bands. Some experimental results are shown to evaluate the gap between the proposed solutions and the theoretically achievable performance.
  • Source
    • "If we want to preserve the reversibility property, we should use a floating-point processor, which is more time-consuming and inefficient . To overcome this problem, some integer color transforms used for approximating noninteger color transforms were developed [2]–[6], [14], [15]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In this correspondence, we introduce a systematic algorithm that can convert any 3 x 3 color transform into a reversible integer-to-integer transform. We also discuss the ways to improve accuracy and reduce implementation complexity. We derive the integer RGB-to-KLA, IV1 V2, YCbCr, DCT, YUV, and YIQ transforms that are optimal in accuracy.
    IEEE Transactions on Image Processing 07/2007; 16(6):1686-91. DOI:10.1109/TIP.2007.896617 · 3.11 Impact Factor
Show more