A variable quantization technique for image compression using integer Tchebichef transform
In the field of image and data compression there is always a need for novel transform coding techniques promising improved reconstruction and reduced computational complexity. The usage of integer adaptation of the popular discrete cosine transform (DCT) with fixed quantization is prevalent in the field of video compression due to its ease of computation and acceptable performance. However, there exist other polynomial-based orthogonal transforms like discrete Tchebichef transform (DTT), which possess valuable properties like energy compaction, but are potentially unexploited in comparison. The influence of specific features, such as the structure and content, of the image on the quality of reconstructed image after decompression is undeniable. This paper aims to harness this aspect and introduces a technique to adapt the quantization performed during compression according to the characteristics of the image block without any additional computational or transmission overhead. The image compression performance of integer DTT and integer DCT, using both variable and fixed quantization, are evaluated and compared.