Binary LBT based Energy Efficient Image Compression for WSN

A wireless sensor network (WSN) is a wireless network that consists of spatially distributed autonomous devices using sensors to cooperatively monitor physical or environmental conditions. One of the major challenge in enabling image transfer service in resource constrained WSN is, it need to process and wirelessly transmit very large volume of data. This will impose severe demands on the battery resources as well as the bandwidth of the wireless sensor network. To minimize the resource constraints in WSN, Binary Lapped Biorthogonal Transform (Binary LBT) based low complexity and low memory image compression algorithm with Modified Golomb Rice code is implemented. DCT used in Binary LBT is computed using only shifting and addition operation because conventional DCT is computed using floating point multiplication, whereas floating point multiplication in hardware implementation consume more power. Binary LBT minimize the blocking artifacts in Discrete Cosine Transform (at low bit rate) and reduce the computational complexity in Discrete Wavelet Transform (DWT) considerably. The proposed Modified Golomb Rice code reduces the number of bits required to represent an image on an average of 10% when compared to Golomb Rice code.