Anotace:
The suitability of 2-dimensional Discrete Wavelet Transform (2D DWT) as a tool in image and video compression is nowadays indisputable. Wavelet based techniques such as JPEG2000 for image compression has a lot more to offer than conventional methods in terms of compression ratio. This paper presents DWT and the use of its compression properties in image processing and briefly describes convolutional implementation of the discrete wavelet transform. More specifically, it deals with lifting implementations of the discrete wavelet transform (LDWT). The main feature of the lifting scheme is that all constructions are derived in the spatial domain. LDWT does not require complex mathematical calculations unlike traditional methods and does not depend on Fourier transforms. The lifting scheme is used to generate second-generation wavelets, which are not necessarily translation and dilation of one particular function. This paper compares two most common types of implementation of LDWT, which are LDWT using a filter banks (FB) 5/3 and 9/7. Within the experiment, the compression properties of the LDWT implementations are compared.