scholarly journals A Color Image Representation Method Based on Non-Symmetry and Anti-Packing Model

2007 ◽  
Vol 18 (11) ◽  
pp. 2932 ◽  
Author(s):  
Yun-Ping ZHENG
Keyword(s):  
Color Image ◽  
Image Representation ◽  
Packing Model ◽  
Representation Method

A Square NAM Representation Method for Binary Images

2011 ◽  
Vol 143-144 ◽  
pp. 755-759
Author(s):  
Jie He ◽  
Yun Ping Zheng ◽  
Hui Guo
Keyword(s):  
Image Representation ◽  
Experimental Results ◽  
Storage Space ◽  
Binary Images ◽  
Representation Model ◽  
Packing Model ◽  
Starting Point ◽  
Representation Method

The Non-symmetry and Anti-packing Model (NAM) is an effective pattern representation model. In this paper, a new NAM image representation method by using the nonoverlapping square subpatterns, which is called the square NAM (SNAM) representation, is proposed. The idea of the SNAM representation is described. The square subpattern has its own significant characteristics when it is compared with other subpatterns such as the triangle and the rectangle, etc. Unlike the general triangle subpattern which needs to record three vertices of the triangle and unlike the rectangle subpattern which needs to record the coordinates of its starting point, length and width, the square subpattern needs to record only its starting point and the side. Therefore, as far as a single record of the square subpattern is concerned, it can save storage space more effectively. The theoretical and experimental results presented in this paper prove the efficiency and the effectiveness of the proposed SNAM representation method for binary images.

An Improved RNAMC Image Representation

2011 ◽  
Vol 143-144 ◽  
pp. 746-749
Author(s):  
Yun Ping Zheng ◽  
Zu Jia Li ◽  
Mudar Sarem ◽  
Qing Hong Yang ◽  
Xiu Xiu Liao
Keyword(s):  
Image Quality ◽  
Image Representation ◽  
Experimental Results ◽  
Reconstructed Image ◽  
Bit Rate ◽  
Gray Image ◽  
Packing Model ◽  
Representation Method ◽  
Improved Algorithm

In this paper, by controlling the ratio of the length and the width of a homogenous block, we proposed an improved algorithm for the gray image representation by using the Rectangular Non-symmetry and Anti-packing Model Coding (RNAMC) and extended shading approach, which is called the IRNAMC image representation method. Also, we present an IRNAMC representation algorithm of gray images. By comparing our proposed IRNAMC method with the conventional S-Tree Coding (STC) method, the experimental results presented in this paper show that the former can significantly reduce the lower bit rate and the number of homogenous blocks than the latter whereas remaining the satisfactory image quality. Also, the experimental results show that by controlling the ratio of the length and the width, we can improve the reconstructed image quality of the RNAMC method.

New Set of Invariant Quaternion Krawtchouk Moments for Color Image Representation and Recognition

2021 ◽  
pp. 2250037
Author(s):  
Gaber Hassan ◽  
Khalid M. Hosny ◽  
R. M. Farouk ◽  
Ahmed M. Alzohairy
Keyword(s):  
Quaternion Algebra ◽  
Color Image ◽  
Image Representation ◽  
Color Images ◽  
Color Channel ◽  
Krawtchouk Polynomials ◽  
Krawtchouk Moments ◽  
Similarity Transformations ◽  
The Stability ◽  
Discrete Moments

One of the most often used techniques to represent color images is quaternion algebra. This study introduces the quaternion Krawtchouk moments, QKrMs, as a new set of moments to represent color images. Krawtchouk moments (KrMs) represent one type of discrete moments. QKrMs use traditional Krawtchouk moments of each color channel to describe color images. This new set of moments is defined by using orthogonal polynomials called the Krawtchouk polynomials. The stability against the translation, rotation, and scaling transformations for QKrMs is discussed. The performance of the proposed QKrMs is evaluated against other discrete quaternion moments for image reconstruction capability, toughness against various types of noise, invariance to similarity transformations, color face image recognition, and CPU elapsed times.

A novel enhanced quantum image representation based on bit-planes for log-polar coordinates

2022 ◽  
Vol 22 (1&2) ◽  
pp. 17-37
Author(s):  
Xiao Chen ◽  
Zhihao Liu ◽  
Hanwu Chen ◽  
Liang Wang
Keyword(s):  
Color Image ◽  
Image Representation ◽  
Polar Coordinates ◽  
Quantum Cost ◽  
Color Information ◽  
Simulation Experiments ◽  
Quantum Image ◽  
Comparison Results ◽  
Bit Planes ◽  
Quantum Image Representation

Quantum image representation has a significant impact in quantum image processing. In this paper, a bit-plane representation for log-polar quantum images (BRLQI) is proposed, which utilizes $(n+4)$ or $(n+6)$ qubits to store and process a grayscale or RGB color image of $2^n$ pixels. Compared to a quantum log-polar image (QUALPI), the storage capacity of BRLQI improves 16 times. Moreover, several quantum operations based on BRLQI are proposed, including color information complement operation, bit-planes reversing operation, bit-planes translation operation and conditional exchange operations between bit-planes. Combining the above operations, we designed an image scrambling circuit suitable for the BRLQI model. Furthermore, comparison results of the scrambling circuits indicate that those operations based on BRLQI have a lower quantum cost than QUALPI. In addition, simulation experiments illustrate that the proposed scrambling algorithm is effective and efficient.

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