In this paper, a new iterative channel estimation algorithm is proposed that exploits channel sparsity in the time domain for DC-biased optical orthogonal frequency division multiplexing OFDM (DCO-OFDM) systems in indoor visible light communications (VLC) in the presence of a clipping noise. A path-based channel model is used, in which the channel is described by a limited number of paths, each characterized by a delay and channel gain. Making use of the pilot symbols, overall sparse channel tap delays and path gains were initially estimated by the compressed sensing approach, in the form of the Orthogonal Matching Pursuit (OMP) and the least-squares (LS) algorithms, respectively. Then a computationally efficient and novel iterative channel estimation algorithm is developed that estimates the clipping noise in the time-domain and compensated for its effect in the frequency-domain. Computer simulation results show that the algorithm converges in maximum two iterations and that yields excellent mean square error (MSE) and bit error rate (BER) performance, outperforming those channel estimation algorithms, which do not have the clipping noise mitigation capability.