This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing image compression workload across a cluster in a wireless sensor network. The main objective of the proposed algorithms is to adopt an energy threshold that is used to implement exchange and/or assignment tasks among sensor nodes. The threshold can be adapted according to the residual energy of sensor nodes, input images, compressed output, and network parameters. We apply the lapped transform technique, which is an extended version of the discrete cosine transform, to the proposed algorithms. We conduct extensive computational experiments to verify our methods and find that the proposed algorithms not only balance total energy consumption among sensor nodes and thus increase the lifetime of the overall network but also reduce block noise in image compression.