Design of a discrete сosine transformation processor for image compression systems on a losless-to-lossy circuit

Today, mobile multimedia systems that use the H.261 / 3/4/5, MPEG-1/2/4 and JPEG standards for encoding / decoding video, audio and images are widely spread [1–4]. The core of these standards is the discrete cosine  transform  (DCT)  of  I,  II,  III  ...  VIII  types  [DCT].  Wide support  in  a  huge  number  of  multimedia applications of the JPEG format by circuitry and software solutions and the need for image coding according to the  L2L  scheme  determines  the  relevance  of  the  problem  of  creating  a  decorrelated  transformation  based  on DCT and methods for rapid prototyping of processors for computing an integer DCT on programmable systems on a FPGA chip. At the same time, such characteristics as structural regularity, modularity, high computational parallelism,  low  latency  and  power  consumption  are  taken  into  account.  Direct  and  inverse  transformation should be carried out according to the “whole-to-whole” processing scheme with preservation of the perfective reconstruction  of  the  original  image  (the  coefficients  are  represented  by  integer  or  binary  rational  numbers; the number of multiplication operations is minimal, if possible, they are excluded from the algorithm). The wellknown  integer  DCTs  (BinDCT,  IntDCT)  do  not  give  a  complete  reversible  bit  to  bit  conversion.  To  encode an image  according  to  the  L2L  scheme,  the  decorrelated  transform must be reversible and implemented in integer  arithmetic,  i. e.  the  conversion  would  follow  an  “integer-to-integer”  processing  scheme  with  a minimum  number  of  rounding  operations  affecting  the  compactness of  energy  in  equivalent  conversion subbands. This article shows how, on the basis of integer forward and inverse DCTs, to create a new universal architecture of decorrelated transform on FPGAs for transformational image coding systems that operate on the principle of “lossless-to-lossy” (L2L), and to obtain the best experimental results for objective and subjective performance compared to comparable compression systems.