Truncating the Coefficients of the Discrete Cosine Transform for Better Digital Image Compression Performance

2021 ◽  
Author(s):  
Poth Miklos ◽  
Zeljen Trpovski
Keyword(s):  
Image Compression ◽  
Discrete Cosine Transform ◽  
Digital Image ◽  
Cosine Transform ◽  
Compression Performance ◽  
Digital Image Compression

JPEG DCT Compressiom

2013 ◽  
Vol 712-715 ◽  
pp. 2542-2545
Author(s):  
Hong Li Jia ◽  
Qiang Liu
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Discrete Cosine Transform ◽  
Digital Image ◽  
Cosine Transform ◽  
Rapid Spread ◽  
Multimedia Technologies ◽  
Joint Photographic Experts Group ◽  
Digital Image Compression ◽  
Further Development

With the rapid spread of image processing applications and the further development of multimedia technologies, compression standards become more and more important. This paper intends to explain JPEG (Joint Photographic Experts Group) compression, which is currently a worldwide standard for digital image compression, is based on the discrete cosine transform (DCT). Based on the research, the paper describes theory and algorithms of the JPEG DCT compression and implements a baseline JPEG codec (encoder/decoder) with MATLAB.

scholarly journals A Fast DCT Algorithm for Watermarking in Digital Signal Processor

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
S. E. Tsai ◽  
S. M. Yang
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Image ◽  
Spatial Data ◽  
Digital Signal Processor ◽  
Block Size ◽  
Digital Signal ◽  
Outer Product ◽  
Cosine Transform ◽  
Digital Image Compression ◽  
Inverse Dct

Discrete cosine transform (DCT) has been an international standard in Joint Photographic Experts Group (JPEG) format to reduce the blocking effect in digital image compression. This paper proposes a fast discrete cosine transform (FDCT) algorithm that utilizes the energy compactness and matrix sparseness properties in frequency domain to achieve higher computation performance. For a JPEG image of8×8block size in spatial domain, the algorithm decomposes the two-dimensional (2D) DCT into one pair of one-dimensional (1D) DCTs with transform computation in only 24 multiplications. The 2D spatial data is a linear combination of the base image obtained by the outer product of the column and row vectors of cosine functions so that inverse DCT is as efficient. Implementation of the FDCT algorithm shows that embedding a watermark image of 32 × 32 block pixel size in a 256 × 256 digital image can be completed in only 0.24 seconds and the extraction of watermark by inverse transform is within 0.21 seconds. The proposed FDCT algorithm is shown more efficient than many previous works in computation.

Sign in / Sign up

Export Citation Format

Share Document